187 Data Segmentation Jobs in Hassan

We are currently hiring for the position of SFMC CDP Data Cloud Developer at Capgemini. Your profile aligns with our requirements, and we would like to share the role details for your review. Role: SFMC CDP Data Cloud DeveloperGrade: C1 Experience Required: 6 to 10 years Location Options: Hyderabad, Bangalore, Chennai, Mumbai, Kolkata, Pune, Noida, Gurugram Role Responsibilities:Drive discussions on SFMC user stories and requirements with stakeholdersArchitect solutions across Marketing and CRM landscapeLead end to end SFMC deliverables for large marketing initiativesCreate use cases, user stories, and proof of conceptsMap Marketing Cloud data models to CRM solutionsDevelop training plans and conduct end user sessionsWork extensively on Email Studio including A B testing, segmentation, personalization, and triggered sendsAct as a key Capgemini representative to bridge business and technical teamsCreate HLD documents and support proposal responses and RFPsProvide best practices for SFMC and CDP implementation and deploymentSupport Salesforce Data Cloud Lead on technical estimations and project planningCoordinate with Salesforce support on upgrades, patches, and configuration best practicesPresent solutions around digital marketing, marketing automation, and data management Technical Skills Required:Minimum 5 years of hands on Marketing Cloud development experienceStrong experience in Salesforce Data Cloud and SFMC integrationsKnowledge of Journey Builder, Automation Studio, Email Studio, Social StudioExperience with Data Cloud modules such as event tracking, API and SDK integration, Salesforce connectors, Apex, JavaScript, and JSONStrong understanding of CDP components including Contact Builder, Audience Builder, Content Builder, and AutomationsCRM integration knowledge with SFDC or other CRM toolsGood understanding of security, roles, access controls, and campaign data governanceExpertise in data architecture, identity resolution, duplicate management, consent management, segmentation, and subscriber managementKnowledge of AMPscript, reporting tools like Tableau or Datorama, and Production deployment processesGood to have experience with mobile push notifications, Interaction Studio, Advertising Studio, and DMPMandatory: Salesforce Data Cloud CertificationGood to Have: SFMC Certification If you are interested in exploring this opportunity, kindly share the following details: Total ExperienceRelevant Experience in SFMC and Data CloudCurrent LocationPreferred LocationCurrent CTCExpected CTCNotice PeriodSalesforce Data Cloud Certification statusUpdated ResumeLooking forward to your response. Thanks & Regards,TA Team Capgemini

As an Analytics Professional at Tredence, you will be part of a global analytics services and solutions company with expertise in Advanced analytics, Data Management, Data Visualization, Big Data, and Machine Learning. Your role will involve partnering with various stakeholders including product, marketing, digital, e-commerce, and customer teams to understand business objectives and translate them into analytical requirements at Fortune 100 Retailers. Key Responsibilities: - Partner with cross-functional stakeholders to translate business objectives into analytical requirements - Gather requirements and understand underlying business problems, serving as the bridge between business needs and analytical solutions - Collaborate with leadership and SMEs to create innovative solutions for business challenges using retail data and analytics - Utilize customer, product, orders, digital clickstream, merchandising, and marketing data to provide effective solutions - Apply advanced analytics and machine learning techniques such as segmentation, AB testing, recommendation engines, and propensity models to drive growth throughout the customer lifecycle Qualifications Required: - Minimum 5+ years of experience in analytics across retail, e-commerce, customer/marketing, product, or digital analytics - Strong expertise in measuring campaign effectiveness, driving test-and-learn programs, and executing A/B testing - Advanced proficiency in SQL and Tableau for data extraction, analysis, and visualization - Proven problem-solving and organizational skills to manage complex projects end-to-end - Excellent communication skills to translate technical insights into clear narratives for stakeholders At Tredence, you will have the opportunity to work with a global team and leverage your skills in analytics to drive impactful solutions for Fortune 100 Retailers.,

Role Overview: As the Senior Manager for S&C Global Network - AI in Healthcare Analytics, your role will involve driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. You will provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. Additionally, you will lead proposals, business development efforts, and coordinate with colleagues to cross-sell/up-sell Life Sciences offerings to existing and potential clients. Key Responsibilities: - Provide strategic advisory services and develop data-driven recommendations to enhance business performance. - Lead proposals, business development efforts, and cross-sell/up-sell Life Sciences offerings. - Collaborate with cross-functional teams to identify opportunities for leveraging data to drive business solutions. - Lead and manage teams to deliver transformative and innovative client projects. - Guide teams on analytical and AI methods and approaches. - Manage client relationships, foster trust, deliver value, and build the Accenture brand. - Drive consulting practice innovation and thought leadership in the healthcare analytics domain. - Support strategies and operating models focused on specific business units, assess competitive responses, and execute transformational change plans aligned with clients" business strategies. Qualifications Required: - Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other quantitative field. - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. - Proven experience in cross-sell/up-sell. - Hands-on experience working with real-world evidence data, R&D clinical data, and digital marketing data. - Experience with handling datasets like Komodo, RAVE, IQVIA, Truven, Optum, SHS, Specialty Pharmacy, PSP, etc. - Experience in building and deployment of Statistical Models/Machine Learning, including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. - Excellent analytical and problem-solving skills with a data-driven mindset. - Strong writing skills to build points of view on current industry trends. - Good client handling skills, demonstrating thought leadership and problem-solving abilities. Additional Details: Opportunity to work on innovative projects and gain career growth and leadership exposure at Accenture.,

As a Senior Product Data Analyst at Blackhawk Network, you will play a critical role in driving the analytics strategy for the Online Commerce Product Line. Your responsibilities will include defining the analytics roadmap, implementing and reporting analytics data, generating insights for optimization, and collaborating with a variety of stakeholders to inform product and business decisions. Key Responsibilities: - Define and own the product analytics roadmap for BHN Online Commerce. - Partner with product managers to brainstorm, research, build hypotheses, and report insights for product decisions. - Lead the instrumentation and ingestion of analytics tags along user journeys. - Debug and validate analytics implementation and data flows. - Create dashboards for new features, experiments, A/B tests, and existing functional areas. - Deliver regular front-end analytics reports to wider stakeholder groups. - Generate insights to identify customer journey gaps, opportunities, and areas for optimization. - Conduct attribution modeling, path analysis, cohort analysis, and CRO experiments to enhance conversion and engagement. - Translate complex data into clear, actionable insights for business and product teams. - Work closely with cross-functional teams to align on KPIs and business outcomes. - Collaborate with data scientists and engineers to improve data pipelines and models. - Present findings and recommendations to technical and non-technical stakeholders effectively. Qualifications: - 5+ years of experience in digital analytics and product data analysis. - Strong expertise in front-end analytics platforms such as Google Analytics (GA4), Adobe Analytics (Omniture), and Adobe suite. - Proficiency in SQL/MySQL with advanced query writing abilities. - Experience with tag management systems like Google Tag Manager and Segment.io. - Ability to design, run, and analyze A/B tests and CRO experiments using tools like VWO, Adobe Target, and Google Optimize. - Strong data visualization skills with Tableau, Looker, Power BI, and Data Studio. - Understanding of customer journey mapping, funnel analysis, campaign ROI tracking, segmentation, and attribution models. - BE/MBA degree preferred. Soft Skills & Core Competencies: - Strong communication and storytelling skills to simplify complex analysis. - Proactive problem solver with a solution-oriented approach. - Excellent stakeholder management and interpersonal skills. - Strong attention to detail with a commitment to data accuracy. - Experience working in global, agile environments with cross-functional teams. Bonus / Nice-to-Have Skills: - Knowledge of JavaScript/DOM debugging for analytics implementation. - Familiarity with server-side tracking, first-party data strategies, and privacy compliance. - Experience with eCommerce platforms and user journey optimization. In this role, you are expected to demonstrate proactiveness, accountability, and a focus on delivering high-quality, well-structured insights and outputs. Timely responses and effective communication across channels will be essential for success in this position.,

As an eCommerce Analytics and Insights Lead at Loyalytics AI, your role will involve defining and monitoring eCommerce KPIs, providing actionable insights, and guiding data-driven decision-making to grow the newly launched eCommerce business. You will work closely with cross-functional teams to analyze data, generate insights, and help in establishing a strong online presence. **Key Responsibilities:** - Define and set up eCommerce KPIs focusing on the customer journey including traffic, conversion, retention, and basket size. - Collaborate with marketing, merchandising, operations, and tech teams to determine data tracking and reporting requirements. - Build dashboards and reports to track site and category performance as well as marketing ROI. - Identify trends, opportunities, and root causes of underperformance in various areas like product availability, pricing, checkout funnel, customer retention, and channel acquisition. - Assist in setting up cohort analysis, customer segmentation, and basic funnel analytics. - Work with eCommerce and data engineering teams to ensure data quality and availability. - Propose data-driven experiments and ideas to drive growth. - Guide business teams in interpreting digital KPIs effectively. **Qualifications Required:** - 3-5 years of experience in eCommerce analytics, preferably within a grocery retail environment. - Proficiency in eCommerce KPIs and analytics frameworks, such as traffic conversion and repeat LTV. - Strong working knowledge of tools like Google Analytics / GA4, Excel, SQL, Power BI, or Tableau. - Experience in handling digital marketing data, CRM data, and product performance data. - Ability to translate business queries into actionable data analysis and present clear insights. - Familiarity with customer journey mapping, funnel conversion, and basket analysis. - Comfortable working in fast-paced, ambiguous, and build-from-scratch environments. - Strong communication and stakeholder management skills across functions. - Proficiency in one of the programming languages like SQL or Pyspark. **Good To Have:** - Experience with eCommerce platforms (e.g., Shopify, Magento, Salesforce Commerce). - Exposure to A/B testing, product recommendation analytics, or personalization logic. - Knowledge of Python/R for deeper analysis (optional). - Experience in setting up tracking infrastructure like GTM or event tagging. Please note that this job description was posted by Shone Joseph from Loyalytics AI.,

As an Assistant Vice President (C12) in the TTS Analytics team at Citi, you will play a crucial role in leading a team of data scientists and analysts. Your responsibilities will include working on various data science projects throughout the year, focusing on business problems across the client life cycle such as acquisition, engagement, client experience, and retention within the TTS business. You will be expected to understand business needs, design, develop, and deploy machine learning models, and effectively communicate insights and recommendations to stakeholders. Key Responsibilities: - Lead a team of data scientists and analysts responsible for the full lifecycle of machine learning model development and deployment - Work on multiple data science projects focusing on business problems across the client life cycle - Design, develop, and deploy machine learning models using various analytical approaches, tools, and techniques - Leverage multiple data sources to provide data-driven insights and machine learning solutions to business and functional stakeholders Qualifications: - Bachelor's Degree with 7-10 years of experience in data analytics, or Master's Degree with 6-10 years of experience in data analytics, or PhD - Marketing analytics experience - Experience in business problems related to sales/marketing strategy optimization, pricing optimization, client experience, cross-sell, and retention - Strong hands-on knowledge of Data Science and Machine Learning, including supervised and unsupervised learning algorithms - Experience with time series models for forecasting and anomaly detection - Experience with unstructured data analysis using NLP/Text Mining techniques - Proficiency in Python/R, PySpark, SQL, ML libraries like Scikit-learn, TensorFlow, and PyTorch - Ability to drive clear communication flow between business stakeholders and the team, translating analytical findings into actionable recommendations Additional Company Details (if present): The TTS Analytics team at Citi provides analytical insights to various functions within the global Treasury & Trade Services business. They focus on driving acquisitions, cross-sell, revenue growth, and improvements in client experience by extracting relevant insights, identifying business opportunities, and building predictive models using big data tools and machine learning algorithms. Please review Citis EEO Policy Statement and the Know Your Rights poster for more information.,

Role Overview: As the Strategic Marketing Director for Waters Division India, you will play a critical role in driving and leading the Go-to-Market efforts in the country. Your expertise in developing, executing, and optimizing sales and marketing strategies tailored to specific customer segments within India will be key to collaborating with cross-functional teams, identifying opportunities, leveraging market insights, and crafting impactful campaigns that drive business growth, brand awareness, and customer loyalty. Key Responsibilities: - Maintain and build small molecule and biosimilar market maps and associated Go-to-Market plans: - Develop a clear understanding of key customers and their products - Leverage install base and existing customer footprint to determine market positioning - Implement a strategy and action plan to gain access to highest volume opportunities - Market Segmentation Strategy: - Develop and implement sub-segmentation strategies based on end customer, behavior, and market opportunity - Define customer needs and pain points across workflows and map those to Waters Right to Win - Customer Insights & Research: - Conduct market research and customer analysis to gain deep insights into country-specific pain points, preferences, and buying behaviors - Drive more personalized campaigns while curating information back into product teams for development and enhancement - Tailored Messaging & Positioning: - Create and adapt messaging, value propositions, and content tailored to specific segments - Ensure relevance and resonance with each group - Sales enablement and implementation: - Work with sales team to deploy segment approaches within each region - Define specific sales activity plans and ensure field teams are equipped to sell and position the portfolio - Cross-Functional Collaboration: - Align segment-specific marketing strategies with business goals and customer-facing initiatives - Performance Metrics & Reporting: - Monitor the performance of country-level campaigns - Use data analytics to measure success and optimize strategies for improved ROI Qualifications: - 20 years of experience as an engagement manager or project manager in management consulting strongly preferred - Bachelors degree in Marketing, Business, or related field (MBA preferred) - Proven track record of developing and executing successful marketing strategies within specific market segments - Strong understanding of data-driven marketing, customer insights, and analytics - Exceptional communication, presentation, and interpersonal skills - Ability to collaborate with cross-functional teams and drive results in a fast-paced environment - Expertise in digital marketing, content creation, and multi-channel campaign execution - Strong leadership skills with the ability to inspire and mentor teams (Note: Omitting the "Company Description" section as it does not provide any additional details about the job role),

As a Sr. Technical Manager specializing in Web Data & Analytics, your role will involve providing strategic guidance, technical direction, and actionable insights to drive business decisions. You will excel in data implementation best practices, collaborate effectively across teams in a global environment, and possess strong communication and execution skills. **Key Responsibilities:** - Lead and mentor the Web Data & Analytics team, ensuring best practices in data collection, governance, implementation, tracking, and reporting. - Collaborate with stakeholders from Web Development, Data Science, and Marketing Leadership to understand analytics needs. - Define and implement a scalable web data architecture for efficient tracking, tagging, and data collection across analytics and marketing platforms. - Provide hands-on expertise in Google Analytics (GA4), Google Tag Manager (GTM), and JavaScript-based tracking solutions. - Develop and enhance a scalable data layer to facilitate standardized and efficient data transmission across platforms. - Track and analyze user journeys, purchase funnels, monitor key performance indicators (KPIs), and deliver insights on user behavior and site performance. - Continuously improve dashboards and data visualizations using Google Data Studio, Tableau, or other BI tools. - Interpret data trends and provide actionable insights to enable data-driven decision-making. - Manage analytics projects, ensuring timely execution of strategic initiatives. - Stay updated with the latest web analytics trends, privacy regulations (GDPR, CCPA), industry standards, and best practices. - Ensure data integrity, accuracy, and consistency across all analytics platforms and reporting tools. - Provide technical guidance and best practices on Google tools for data collection, tagging, and reporting. - Develop compelling data reports, dashboards, and visualizations with supporting narratives for senior leadership presentations. **Qualifications:** - 10+ years of experience in Web Analytics, with at least 2+ years in a managerial or leadership role. - Strong understanding of digital marketing analytics, attribution modeling, and customer segmentation. - Expertise in web data architecture, tracking strategy development, and data layer design. - Hands-on experience with event-driven tracking, structured data layers, and tagging frameworks. - Proven expertise in Google Analytics (GA4), Google Tag Manager (GTM), and web tracking tools such as Amplitude, Glassbox, or similar technologies. - Familiarity with audience segmentation through Customer Data Platforms (CDPs) or Google Analytics. - Deep understanding of JavaScript, HTML, and CSS, with the ability to debug and troubleshoot tracking issues. - Proficiency in SQL and familiarity with scripting languages such as Python or JavaScript for automation. - Experience managing BigQuery or other marketing databases, including data extraction, transformation, and analysis. - Strong analytical skills in integrating user data from multiple sources, user behavior analysis, and A/B testing. - Ability to generate and present actionable insights that drive Conversion Rate Optimization (CRO). - Excellent communication and presentation skills, with the ability to translate complex data into meaningful business insights. - Strong project management skills, with the ability to manage multiple priorities and deadlines. - Bachelor's degree in Marketing, Computer Science, or a related field. - Advanced certification in GA4 is a plus. Feel free to write to rajeshwari.vh@careerxperts.com to get connected! #HighBarOfEntry,

Role Overview: You will be joining Analytical Wizards, which is part of the Definitive Healthcare family. The company values innovation and maintains an open, friendly culture. As a Data Scientist / Senior Data Scientist, you will be responsible for utilizing your strong coding skills and experience in data handling and wrangling using Python. Your role will involve working on projects related to advanced analytics, report generation, metrics extraction from complex datasets, and solution workbenches. You will be using various quantitative and analytical techniques to assist clients in making informed business decisions. Additionally, you will be participating in sales and marketing projects, focusing on areas such as multi-channel marketing effectiveness, campaign performance analysis, and designing experiments. Key Responsibilities: - Expertise in custom projects centered around prescription and claims-based reporting and modeling - Collaborate with Product and Customer Success teams to provide insightful analyses to clients - Generate deliverables to support customer engagements - Work with team members to implement optimized solutions - Contribute to internal projects and processes - Collaborate with the global team to create deliverables - Mentor junior analysts and promote best practices - Independently scope client requests Qualification Required: - Data Experts with 2 - 5 years of experience specializing in Python - Educational background in Engineering, Operations Research, Econometrics, and/or Statistics - Hands-on experience with Python is mandatory - Strong interpersonal skills, excellent presentation, and communication skills - Proficiency in Microsoft Excel and SQL - Ability to work with large datasets, think creatively, evaluate current processes, and suggest improvements - Knowledge of Pharma datasets is advantageous Additional Company Details: Analytical Wizards, a leading Analytics Software Development company under the Definitive Healthcare family, is headquartered in New Jersey with a software development and delivery center in Bangalore. The company's primary focus is on the Healthcare Industry, where they develop core data science products to help clients extract unique insights from big data. Their products utilize advanced algorithms in artificial intelligence and machine learning and are used by top pharma and biotechnology companies worldwide. Analytical Wizards has been recognized as one of the fastest-growing private companies in the USA. The company's work culture is employee-friendly, collaborative, innovative, fast-paced, and conducive to learning. (Note: The ISMS Responsibilities section has been omitted as it contained specific internal security policies and processes.),

As an AVP - Data Science at GenAI, you will be responsible for driving advanced analytics opportunities in the BFSI sector. Your role will involve leading end-to-end project delivery, stakeholder engagement, and team management to deliver high-impact solutions for Indian clients. **Key Responsibilities:** - Build strong partnerships with BFSI clients and channel partners - Communicate methodologies effectively to drive stakeholder confidence - Scope, plan, and deliver end-to-end analytics projects - Design and deploy high-impact data science and GenAI models - Mentor, coach, and upskill junior data scientists - Ensure adherence to SOPs, documentation, and governance frameworks **Qualifications Required:** - 10+ years of experience in advanced analytics - Graduate/Postgraduate degree from Tier-I colleges - Ability to design and review new solution concepts - Strong understanding of statistical concepts - Proficiency in Python (NumPy, Pandas, Scikit-learn, etc.) - Expertise in handling massive datasets using tools such as Apache Spark, Vaex, Dask - Hands-on experience in building and deploying models in various areas such as promotion optimization, NLP, clustering, fraud detection, neural networks, etc. - Experience with cloud platforms like Azure, GCP, AWS - Familiarity with ML-Ops pipelines for automated model training and deployment If you join GenAI, you will have the opportunity to work in a dynamic environment where you can contribute to cutting-edge analytics solutions for the BFSI sector.,

Role Overview: You will be responsible for leading AI-driven after-sales logistics operations focusing on data analytics. Your main tasks will involve designing, developing, and implementing machine learning models to enhance forecasting accuracy, inventory optimization, demand prediction, and operational efficiency in spare parts warehouse operations. Key Responsibilities: - Develop and deploy machine learning models for spare parts demand forecasting, inventory optimization, predictive replenishment, stock-out prevention, supplier lead-time analysis, order pattern analysis, and anomaly detection. - Utilize AI techniques like NLP, computer vision, and LLMs for automated parts identification, semantic search in parts catalogs, and intelligent chatbot assistants. - Analyze operational data to identify process bottlenecks and recommend data-driven improvements. - Collaborate with cross-functional teams to implement scalable AI solutions, integrate data pipelines from ERP/WMS systems, prepare dashboards using tools like Power BI or Tableau, and research AI-driven automation tools for spare parts logistics. - Design and deploy automation scripts using Python, SQL, or RPA tools to enhance efficiency in warehouse management. Qualification Required: - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Business, or related field. - 7+ years of experience with at least 3 years specializing in Artificial Intelligence/Machine Learning development and working with Microsoft Power Platform. - Hands-on experience with chatbots/AI assistants, automation scripts, Power BI, Python, ML libraries, LLMs, NLP frameworks, and agile project lifecycles. - Proficiency in stakeholder communication, risk management, and governance frameworks. - Preferred qualifications include Microsoft Power Platform certification, experience with process mining, and change management. - Strong technical knowledge in integrating AI models, SQL data pipelines, BI dashboards, and warehouse automation systems. - In-depth understanding of spare parts logistics, warehouse operations, SKU segmentation, inventory control, lead-time management, safety stock strategies, and warehouse performance KPIs. Company Details: Omitted as no additional details of the company are mentioned in the JD.,

As a Senior Analyst - Data Science at our technology-led healthcare solutions provider, you will play a crucial role in leading analytical solutioning and model development in the pharmaceutical commercial analytics domain. Your responsibilities will include partnering with cross-functional teams and client stakeholders to gather business requirements, designing and implementing Decision Engine workflows, analyzing complex datasets, and developing predictive models for various use cases. Additionally, you will mentor junior team members, stay updated with industry trends, and ensure data quality through systematic checks. Key Responsibilities: - Partner with cross-functional teams and client stakeholders to gather business requirements and translate them into robust ML/analytical solutions. - Design Decision Engine workflows to support Next Best Action recommendations in omnichannel engagement strategies. - Analyze large and complex datasets from various sources like APLD, sales, CRM, market share, patient claims, and segmentation data. - Develop, validate, and maintain predictive models for use cases such as patient journey analytics, HCP targeting, sales forecasting, risk scoring, and marketing mix modeling. - Implement MLOps pipelines using tools like Dataiku, Git, and AWS services for scalable and repeatable deployment. - Lead and mentor junior analysts and data scientists in coding best practices, feature engineering, and cloud-based workflows. - Stay up to date with industry trends, regulatory compliance, and emerging data science techniques relevant to life sciences analytics. Qualifications Required: - 5 years of hands-on experience in pharmaceutical commercial analytics with exposure to cross-functional brand analytics and ML modeling. - Proficiency in data platforms like Snowflake, Dataiku, AWS, PySpark, Python, and SQL. - Experience with MLOps practices, version control, model monitoring, and automation. - Strong understanding of pharmaceutical data assets and proficiency in ML algorithms and key use cases. - Familiarity with dashboarding tools like Tableau or PowerBI is a plus. - Strong communication and documentation skills to convey findings effectively to technical and non-technical audiences. If you are excited about the opportunity to work at the intersection of healthcare and technology, and meet the qualifications mentioned above, we encourage you to apply for this role.,

As a Senior Associate in data analysis at PwC, you will play a crucial role in leveraging data to drive insights and support clients in making informed business decisions. Your responsibilities will include utilizing advanced analytics techniques to extract insights from large datasets, manipulating data, creating visualizations, and employing statistical modeling to solve complex business problems. Key Responsibilities: - Proven expertise in supply chain analytics including demand forecasting, inventory optimization, logistics, segmentation, and network design - Hands-on experience with optimization methods like linear programming, mixed integer programming, scheduling optimization, and using third-party optimization solvers such as Gurobi - Proficiency in forecasting techniques like Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats, and machine learning techniques (supervised and unsupervised) - Strong command of statistical modeling, testing, and inference - Proficient in GCP tools like BigQuery, Vertex AI, Dataflow, and Looker - Building data pipelines and models for forecasting, optimization, and scenario planning - Strong skills in SQL and Python programming, with experience deploying models in the GCP environment - Knowledge of orchestration tools like Cloud Composer (Airflow) Nice to Have: - Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools like Cloud Composer - Strong communication and stakeholder engagement skills at the executive level Qualifications Required: - BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA from a reputed institute,

As a Senior Data Scientist specializing in computer vision, you will play a crucial role in designing, implementing, and deploying deep learning models for image classification, object detection, segmentation, and video analytics. Your responsibilities will involve handling large-scale image/video datasets, implementing MLOps practices, collaborating with engineering teams, and providing technical mentorship to junior team members. Key Responsibilities: - Design, implement, and deploy deep learning models for image classification, object detection, segmentation, and video analytics. - Handle large-scale image/video datasets with preprocessing, augmentation, and feature extraction. - Implement MLOps practices including model versioning, CI/CD pipelines, and automated deployment. - Collaborate with engineering teams to integrate models into production systems. - Provide technical mentorship to junior team members. Required Skills & Expertise: - Strong programming skills in Python. - Hands-on experience with TensorFlow, PyTorch, or Keras. - Familiarity with Databricks notebooks, MLflow, Delta Lake. - Solid understanding of CNNs, transfer learning, ViT, and other computer vision algorithms. - Experience with Azure cloud ecosystem and UNIX/Linux scripting. - Exposure to NLP techniques is a plus. Soft Skills: - Strong analytical and problem-solving abilities. - Excellent written, verbal, and visual communication skills. - Ability to collaborate effectively with cross-functional teams. Education: - B.E./B.Tech/M.Tech/MCA in Computer Science, ECE, EE, or related field. - Masters in AI / Deep Learning / Computer Vision is highly preferred. In this role, you will have the opportunity to work on cutting-edge AI/ML projects in computer vision, be part of a collaborative and innovative work environment, and have the chance to mentor and grow your career in data science and AI.,

Role Overview: As an Anti Money Laundering (AML) Independent Validation (IV) analyst at Citi Analytics & Information Management team in Bangalore, you will be responsible for conducting Independent Validation on AML Scenario validation, complex statistical analysis, data visualizations, and data processing based on globally consistent standards and regulatory guidelines. Your role will involve presenting findings in a clear and understandable manner both in writing and verbally, ensuring high levels of integrity, quality, and attention to detail. Key Responsibilities: - Perform Independent Validation of AML Scenarios, KPI reports, AML Cards Scenarios, etc., following the AML Global Methodology and compliance with governance policy and OCC requirements - Apply statistical methods to organize, analyze, and interpret data for validations - Present validation outcomes to sponsors and stakeholders, providing data pulls and reports directly from Oracle Database and EAP - Write efficient SQL and PL/SQL queries in a complex Large-Scale database environment - Evaluate validation assumptions, data completeness, limitations, and methodology of scenarios/tools being validated - Prepare validation reports in a detailed and structured manner, including clear conclusions based on the analysis performed - Use visualization techniques to display data and analysis results in presentations understandable by non-technical readers - Conduct annual validation performance assessments and perform above the Line testing for transaction monitoring thresholds - Ensure Data Quality and Reliability Qualifications: - 3-5 years of experience in the Analytics Industry - Previous experience with Financial Services companies - Experience with Mantas and AML monitoring systems is a plus - Good working knowledge of SAS, SQL, Hive, Python, PySpark, Impala, Excel & VBA - Basic knowledge of Big Data/Hadoop architecture and Segmentation, Clustering techniques - Strong Statistics and Data Analytics academic background - Experience in reporting analysis results and presenting findings clearly - Ability to communicate technical requirements and work well with a variety of people - Self-motivated with a high desire for self-development and learning - Masters in a numerate subject such as Mathematics, Operational Research, Business Administration, Economics (Note: Additional details about the company were not present in the provided job description.),

As a Senior Data Analyst with 5-8 years of experience, you will play a crucial role in our data-driven decision-making processes at our Bangalore office. Your primary responsibilities will include developing data pipelines, creating interactive Tableau dashboards, and delivering actionable insights to drive business decisions. Collaboration with both business and technical teams is essential to ensure data accuracy, accessibility, and integrity. Key Responsibilities: - Analyze structured and semi-structured data to identify trends, insights, and opportunities. - Design and create interactive Tableau dashboards and reports for business stakeholders. - Interpret data to pinpoint key metrics, patterns, and anomalies. - Assist in the development and maintenance of ETL pipelines using Airflow, Databricks, and Python. - Ensure the timely and accurate flow of data across various systems. - Contribute to the creation and deployment of fundamental machine learning models for tasks such as forecasting, segmentation, or classification. - Write and optimize PL/SQL queries for efficient data extraction and transformation. - Perform data validation and maintain data consistency across all reports and dashboards. - Work closely with product, business, and engineering teams to understand their data requirements. - Translate complex business questions into analytical tasks and present clear, data-driven narratives. - Support initiatives to enhance data accuracy, integrity, and overall governance. - Monitor data pipelines and proactively troubleshoot any emerging issues. Required Skills & Experience: - 5-8 years of experience in data analysis or a comparable role. - Proficiency in SQL/PL-SQL, Python, and Tableau. - Familiarity with cloud-based data platforms like Databricks, AWS, or GCP. - A solid understanding of machine learning concepts and practical experience with simple ML models (e.g., regression, classification) in Python. - Strong analytical mindset with a keen attention to detail. - Excellent ability to communicate insights effectively through visualizations and storytelling. - Knowledge of data quality best practices and pipeline monitoring techniques. If you are detail-oriented and skilled in data analysis, this is the perfect opportunity for you to contribute to our data-driven decision-making processes. You will have the chance to work with tools such as Databricks, Python, PL/SQL, and Tableau while collaborating closely with business and technical teams to ensure data accuracy, accessibility, and integrity. Apply now to join our team and make a significant impact!,

As a Data Annotation & AI Support Associate, your role will involve assisting the AI/ML team in preparing high-quality datasets for machine learning projects. You will work with various data types including images, videos, spreadsheets, and basic Python scripts to ensure data labelling and quality verification are done accurately. Your responsibilities will include: - Image & Video Annotation: - Drawing bounding boxes, segmentation polygons, and keypoints. - Labeling objects following internal annotation guidelines. - Reviewing and correcting previously annotated samples. - Watching raw videos to identify usable clips and flag anomalies. - Data Cleaning & Quality Control: - Removing duplicates, corrupted files, and poor-quality samples from datasets. - Validating dataset folder structures, filenames, metadata, and formats. - Maintaining organized dataset versions (raw, processed, clean). - Reviewing footage to determine the validity and quality of clips. - Excel & Spreadsheet Analysis: - Sorting, filtering, and inspecting data using Excel/Google Sheets. - Identifying anomalies, inconsistencies, missing values, and outliers. - Computing basic statistics like mean, median, and mode. - Preparing small summary reports for the AI team. - Python Utility Tasks (Good to Have): - Running preprocessing or conversion scripts. - Writing basic Python code for automating repetitive tasks. - Using Jupyter notebooks or CLI tools for data exploration. Qualifications required for this role include: - Experience with annotation tools such as CVAT, Label Studio, Roboflow, VGG Annotator, etc. - Strong attention to detail, especially during repetitive data review tasks. - Comfort working with Excel/Google Sheets and large datasets. - Basic understanding of Python, NumPy, or Pandas is preferred. - Ability to work with large files, cloud storage, and structured folders. It would be beneficial if you have prior experience with AI/ML data preparation or annotation, understanding of object detection formats like YOLO, COCO, Pascal VOC, familiarity with dataset validation and quality-check techniques, and exposure to Git, Linux, or Jupyter Notebooks. Additionally, soft skills required for this role include strong communication, collaboration with engineers, reliability, consistency, responsibility in task execution, and an ownership mindset focusing on delivering high-quality work.,

Role Overview: You will be part of the MarTech Data Engineering POD supporting a large-scale ESP migration program from Oracle Responsys to Adobe Journey Optimizer. Your role will involve designing, building, and maintaining data pipelines to enable real-time marketing campaign execution and advanced targeting capabilities across various channels. Key Responsibilities: - Design and develop data ingestion, transformation, and orchestration pipelines using GCP services such as BigQuery, Dataflow, Cloud Composer (Airflow). - Implement and maintain data integrations between Adobe Experience Platform and data lake, ensuring high performance and scalability. - Build and optimize ETL/ELT workflows to support campaign orchestration, preference logic, and audience segmentation. - Implement data quality checks, monitoring, and exception handling frameworks for clean and reliable data. - Collaborate with the team to translate campaign archetypes into data pipelines and orchestration rules. - Support performance tuning, data reconciliation, and defect resolution during testing and hypercare phases. - Participate in Agile ceremonies, sprint reviews, and deployment planning. Key Skills: - Strong hands-on experience in GCP services: BigQuery, Dataflow, GCS, Cloud Composer (Airflow). - Proficiency in SQL for data profiling, transformation, and performance optimization. - Proficiency in Python for pipeline automation, scripting, and orchestration. - Experience in building batch and streaming data pipelines. - Exposure to working with marketing or customer engagement platforms is a plus. - Understanding of data quality, logging, monitoring, and alerting best practices. Preferred Skills: - Experience in Airflow DAG development for complex data pipelines. - Familiarity with MarTech platforms such as Adobe Experience Platform or similar ESPs. - Knowledge of data modeling for campaign orchestration and audience segmentation. - Experience with CI/CD and DevOps principles for data deployments. - Strong troubleshooting and performance tuning skills. Qualification Required: - Bachelors or Masters degree in Computer Science, Information Technology, or a related field. - GCP certifications (e.g., Professional Data Engineer) preferred but not mandatory. If you are passionate about leveraging technology to drive business innovation, possess excellent problem-solving skills, and thrive in a dynamic environment, we encourage you to apply for this exciting opportunity. Join us in shaping the future of data analytics and making a meaningful impact in the industry.,

As a Data Scientist at our company, you will be responsible for supporting the development and deployment of machine learning models and analytics solutions aimed at improving decision-making across the mortgage lifecycle. Your key responsibilities will include: - Developing and maintaining machine learning models and statistical tools for various use cases such as risk scoring, churn prediction, segmentation, and document classification. - Collaborating with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives. - Translating business questions into modeling tasks and contributing to the design of experiments and success metrics. - Assisting in building and maintaining data pipelines and model deployment workflows in partnership with data engineering. - Applying techniques such as supervised learning, clustering, and basic NLP to structured and semi-structured mortgage data. - Supporting model monitoring, performance tracking, and documentation to ensure compliance and audit readiness. - Contributing to internal best practices and participating in peer reviews and knowledge-sharing sessions. - Staying current with developments in machine learning and analytics relevant to mortgage and financial services. Qualifications required for this role include: - Minimum education required: Masters or PhD in engineering/math/statistics/economics, or a related field - Minimum years of experience required: 2 (or 1, post-PhD), ideally in mortgage, fintech, or financial services - Required certifications: None - Experience working with structured and semi-structured data; exposure to NLP or document classification is a plus. - Understanding of model development lifecycle, including training, validation, and deployment. - Familiarity with data privacy and compliance considerations (e.g., ECOA, CCPA, GDPR) is preferred. - Strong communication skills and ability to present findings to technical and non-technical audiences. - Proficiency in Python (e.g., scikit-learn, pandas), SQL, and familiarity with ML frameworks like TensorFlow or PyTorch.,

Role Overview: As a Senior Machine Learning / Data Engineering / Data Science Engineer specializing in Credit Risk, you will be responsible for building Next-Generation AI-Powered Credit Decisioning Systems on AWS. You should have at least 5 years of experience and a deep understanding of credit risk modeling, lending workflows, and end-to-end credit decisioning systems. Your role will involve designing and deploying production-grade models, data pipelines, APIs, and governance frameworks to support modern lending products. Key Responsibilities: - Develop and validate credit scoring, PD/LGD/EAD, and behavioral/collections models. - Build rule-based + ML hybrid underwriting engines and challenger models. - Design and implement feature stores, scorecards, segmentation logic, and reason-code/XAI frameworks. - Build large-scale ETL/ELT pipelines using AWS and open-source stacks (Airflow, Spark, Trino, EKS, S3, EC2). - Implement robust data quality, lineage tracking, anomaly detection, and incremental loading. - Optimize compute and storage for performance, reliability, and cost (including Graviton). - Deploy models using MLflow, Flask, or FastAPI. - Implement model monitoring, drift detection, CI/CD, and automated retraining workflows. - Ensure compliance with Basel III, SR 11-7, GDPR, PDPA using explainability and governance tools. - Build dashboards for model performance, data quality, and underwriting analytics. - Build and deploy APIs using API Gateway, Lambda, ECS/Fargate, or EKS. - Integrate ML scoring pipelines with LOS/LMS, credit bureaus, and partner systems. - Conduct demos, PoCs, and technical workshops with clients. - Translate business problems into credit product workflows, decision rules, and risk logic. Qualifications Required: - 5+ years in Machine Learning, Data Engineering, or Data Science. - Hands-on experience building credit risk, fraud, or behavioral ML models. - Strong expertise in Python, PySpark, SQL, and ML frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch). - Experience with Spark, Hadoop, Kafka, Trino/Presto. - Strong understanding of credit underwriting workflows, lending KPIs, and risk decisioning. - Experience building and deploying ML scoring APIs. - Familiarity with MLOps best practices and production ML systems. - Strong grasp of data governance, regulatory compliance, and model documentation. Additional Company Details: N/A,