11 Logistic Regression Jobs in Faridabad

About Taggd: Taggd is a digital recruitment platform that provides Ready-to-Hire talent to India Inc. Combining the power of human knowledge and data, Taggd has successfully fulfilled talent mandates of more than 100+ clients and ensured hiring managers success for half a million jobs from over 14+ sectors. With a vision to fill 1 million Jobs through our talent platform by 2030, we strive to connect people with people, people with companies, and people with opportunities. Just right. Every time. For more information pls visit www.taggd.in About the Position: Designation: Machine Learning Engineer Domain Expertise: AI/ML Job Location: Gurgaon Working Days: 5 days (Hybrid) About the Role: At Taggd, our people are our most important resource. Were looking for a highly skilled recruiter to become one of them, and to help us find them. The ideal candidate will have prior experience in recruitment or talent acquisition, with knowledge of screening, interviewing, and hiring practices. If you have a passion for finding untapped talent, driving company growth, and helping individuals find promising careers, we want to hear from you. Job Requirements: Education: Btech Experience: 2-5 years Desired Competencies: Must have skills: Machine Learning, Python, LLM, Prompting Good to have: Predictive/ Statistical Modeling, Recommender System, Text Mining / Optimisation, Elasticsearch Must have solid hands-on experience python with data analysis and representation of the same. At least 3 years of relevant experience with Statistical Modelling, Predictive Analytics or Recommender Systems At least 1 year of relevant experience with LLM and prompting Decent Understanding of Machine Learning Algorithms and Neural Networks Prior experience with NLP and Elasticsearch is advantageous Expert in Logistic Regression based as well as other classification-based model building, segmentation techniques, clustering Desired Good knowledge of big data platforms and tools

As a Senior ML Engineer, you will apply machine learning engineering and applied data science techniques to design, train, and evaluate models that directly impact industrial performance, working closely with engineers and the Product Operations team. This is a hands-on role for someone who thrives on ownership, experimentation, and delivering real-world impact. You will play a key role in advancing the intelligence and reliability of industrial processes powered by Batch AI. Responsibilities: - Design, train, and validate machine learning models that improve process performance and stability in concrete batching operations. - Lead end-to-end model development, from data exploration and feature engineering to deployment and validation. - Define and implement retraining and validation strategies that ensure continuous performance improvement. - Work closely with engineers to ensure models integrate efficiently with production systems in Azure and AWS environments. - Propose data selection and quality control methods to improve training representativity. - Contribute to the monitoring and evaluation approach for ongoing model health. - Document methodologies, experiments, assumptions, and decisions to maintain clarity and reproducibility. - Collaborate with team members, the Product Operations team, and other stakeholders as needed to support large-scale deployment. Qualifications: Must-Have: - BSc or MSc in Data Science, Applied Mathematics, Computer Science, or equivalent practical experience. - 5+ years of hands-on experience in applied machine learning, with a focus on regression, forecasting, or optimization. - Proven experience in production-grade ML pipelines, from experimentation to deployment. - Strong grasp of data science concepts such as cross-validation, quantile modeling, and model safeguard techniques. - Strong background in Python and data science libraries, with the ability to write clean, efficient, and production-ready code. - Experience using modern development tools and practices, including Git and related workflows, code review processes, automated testing, and CI/CD pipelines. - Solid understanding of data lifecycle management, including time-series feature engineering and retraining strategies. - Experience with ML model monitoring, versioning, and continuous retraining frameworks. - Familiarity with cloud ML ecosystems (Azure or AWS). - Comfortable documenting and presenting analytical findings to mixed technical and non-technical audiences. - Effective communication and collaboration skills. - Self-driven, organized, and able to deliver with minimal supervision. Nice-to-Have: - Experience with Azure ML, CosmosDB, Service Bus, and Kubernetes. - Experience with AWS SageMaker, ECS Fargate, SQS/EventBridge, and DocumentDB. - Exposure to industrial data from manufacturing equipment, batching systems, or other IoT-connected process control environments such as manufacturing, logistics, or energy sectors. - Experience applying software development and engineering best practices, including architectural, design, and coding principles. - Experience with containerized workloads (Docker). GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world's largest and most forward-thinking companies. Since 2000, they have been at the forefront of the digital revolution - helping create some of the most innovative and widely used digital products and experiences. Today, they continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.,

Role Overview: You will be a QA SCM Consultant at Opkey, responsible for testing Oracle Fusion SCM modules such as Planning, Costing, and Service Logistics. Your role will involve ensuring data accuracy, functional compliance, and end-to-end business flow validation across various SCM processes. Key Responsibilities: - Perform functional, regression, integration, and UAT testing for Oracle Fusion SCM modules. - Validate end-to-end business flows across Planning, Costing, and Service Logistics. - Convert business requirements into comprehensive test cases and scenarios. - Collaborate with Product Managers, Developers, and Business Analysts for testing SaaS agile releases. - Participate in sprint planning, grooming, QA estimation, and test planning. - Document defects clearly and maintain detailed test reports, execution logs, and regression packs. - Support UAT with business stakeholders for a smooth production rollout. Qualification Required: - 3-5 years of QA experience in Oracle Fusion SCM applications. - Strong functional knowledge in Planning, Costing, and Service Logistics modules. - Experience in creating test plans, test cases, and traceability matrices. - Good understanding of SaaS release cycles, cloud-based testing, and Agile/Scrum environments. - Strong problem-solving and analytical skills with attention to detail. - Experience with automation testing tools like Opkey, Selenium, OATS, or cloud-based QA platforms is a plus. - Knowledge of Oracle Cloud changes, quarterly updates, and API testing (Postman/REST) is beneficial. Company Additional Details: At Opkey, we empower enterprises with cutting-edge, agentic AI-powered automation to unlock their ERP investments" full potential. Our platform ensures continuous assurance from initial deployment to long-term digital transformation, helping organizations modernize with confidence and agility. With a collaborative culture and high learning opportunities, you will work on impactful features used by global enterprise customers.,

As a Teaching Assistant for the Data Science and Data Analyst Offline Programs, you will have the opportunity to support learners in their journey from foundational analytics to advanced technologies like Deep Learning, NLP, and Generative AI. Your role will involve conducting doubt-clearing sessions, guiding hands-on activities, supporting project development, and creating an engaging learning environment in collaboration with instructors. Key Responsibilities: - Conduct regular doubt-clearing sessions covering various core topics such as Python, statistics, SQL, Excel, data visualization, machine learning, deep learning, NLP, and generative AI. - Organize hands-on exercises, case studies, and model-building challenges using real-world datasets and tools like Pandas, Scikit-learn, Tensorflow, PyTorch, Hugging Face, and OpenAI APIs. - Monitor learner progress, identify gaps, and provide personalized support across foundational and advanced AI concepts. - Foster an engaging classroom environment by encouraging curiosity, experimentation, and collaboration. Sub-Goals: - Strengthen learners" understanding in analytical and AI-driven topics through practice-oriented sessions. - Help students build confidence in handling complex problems using classical and modern AI tools. - Collaborate with instructors to support learners in achieving key milestones such as Exploratory Data Analysis, Machine Learning Projects, NLP Pipelines, and Generative AI Capstone Projects. - Review and provide feedback on assignments involving regression, classification, neural networks, chatbot building, and generative model applications. - Guide learners in developing a diverse portfolio demonstrating skills in data analysis, business problem-solving, and AI innovation. - Ensure students gain hands-on exposure to AI applications like image generation, language modeling, and real-time analytics. Sub-Goals: - Equip students with practical, in-demand skills for roles such as Data Analyst, Business Analyst, Data Scientist, and AI Engineer. - Bridge theoretical knowledge with practical implementation using industry-adopted tools and frameworks. - Maintain batch records, coordinate batch operations, resolve operational issues, and contribute to refining teaching methods for better delivery of advanced AI concepts. Sub-Goals: - Ensure smooth logistics and academic execution across beginner and advanced AI learning tracks. - Contribute actively to improving AI curriculum effectiveness and learner engagement strategies. Qualifications Required: - Education: Bachelor's degree in Computer Science, Engineering, Statistics, or related field (or equivalent industry experience). - Technical Skills: Strong foundation in Python, SQL, Excel, Statistics, data visualization, machine learning. Proficiency in deep learning frameworks, NLP libraries, and generative AI tools. - Hands-on Experience: Developing and deploying ML/DL models, building dashboards, NLP pipelines, and experimenting with generative models. - Communication: Ability to explain fundamental and advanced AI concepts in an engaging way. - Mentorship: Passion for teaching and mentoring learners. - Collaboration & Time Management: Ability to balance academic guidance, operational tasks, and team collaboration effectively. Preferred Qualifications: - Prior experience in mentoring learners in data fields. - Project or teaching experience in deep learning, NLP applications, or generative AI. - Familiarity with collaborative coding, cloud-based notebooks, and APIs for deploying AI solutions. - Participation in AI hackathons, case competitions, or publication of models/projects on platforms like Kaggle or Hugging Face Hub.,

As a Solution Architect/Business Development Manager at NTT DATA, your role involves driving business growth and delivering innovative solutions in the field of AI/ML. You will be responsible for assessing client business requirements, designing technical solutions, recommending AI/ML approaches, and collaborating with delivery organizations to implement end-to-end solutions. Key Responsibilities: - Business Requirement Analysis: Assess client's business requirements and convert them into technical specifications that meet business outcomes. - AI/ML Solution Design: Recommend the right AI/ML approaches to meet business requirements and design solutions that drive business value. - Opportunity Sizing: Size the opportunity and develop business cases to secure new projects and grow existing relationships. - Solution Delivery: Collaborate with delivery organizations to design end-to-end AI/ML solutions, ensuring timely and within-budget delivery. - Costing and Pricing: Develop costing and pricing strategies for AI/ML solutions, ensuring competitiveness and profitability. - Client Relationship Management: Build and maintain strong relationships with clients, understanding their business needs and identifying new opportunities. - Technical Leadership: Provide technical leadership and guidance to delivery teams, ensuring solutions meet technical and business requirements. - Knowledge Sharing: Share knowledge and expertise with the team, contributing to the development of best practices and staying up-to-date with industry trends. - Collaboration: Work closely with cross-functional teams, including data science, engineering, and product management, to ensure successful project delivery. Requirements: - Education: Master's degree in Computer Science, Engineering, or related field - Experience: 10+ years of experience in AI/ML solution architecture, business development, or a related field - Technical Skills: - Strong technical expertise in AI/ML, including machine learning algorithms, deep learning, and natural language processing. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Experience with cloud-based AI/ML platforms and tools (e.g., AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform). - Soft Skills: - Excellent business acumen and understanding of business requirements and outcomes. - Strong communication and interpersonal skills, with the ability to work with clients and delivery teams. - Business Acumen: Experience with solution costing and pricing strategies. - Strong analytical and problem-solving skills, with the ability to think creatively and drive innovation. Nice to Have: - Experience with Agile development methodologies. - Knowledge of industry-specific AI/ML applications (e.g., healthcare, finance, retail). - Certification in AI/ML or related field (e.g., AWS Certified Machine Learning Specialty). Location: Delhi or Bangalore Workplace Type: Hybrid Working NTT DATA is an Equal Opportunity Employer.,

Role Overview: You will be part of the Home team within the Product Analytics and Experimentation organization at Expedia Group. Your role will involve providing insights and measurement to support the Product team in making informed decisions about product features. You will work with stakeholders up to the Senior Manager level and apply analytical capabilities to solve business problems. Key Responsibilities: - Extract and integrate data from multiple sources for model building and analytics. - Design and recommend simple and complex experiments (e.g., A/B, pre/post, causal impact) to address business questions. - Build basic models (e.g., linear, logistic, clustering) and select appropriate data structures and formats. - Develop and maintain basic data pipelines and workflows to support modeling tasks. - Collaborate with stakeholders to refine project scope and requirements. - Apply business knowledge to shape modeling questions, select features, and guide decisions. - Deliver clear data stories and visualizations to support decision-making. - Automate recurring reporting and dashboarding tasks across multiple platforms. - Share documentation, code, and project artifacts with relevant audiences. - Communicate project goals, methods, insights to both technical and non-technical stakeholders. - Collaborate with analytics peers through brainstorming, peer review, and knowledge sharing. - Train stakeholders to use dashboards and self-service tools and promote data literacy. - Troubleshoot and resolve data issues to ensure efficient query and pipeline performance. - Uphold best practices for code sharing and documentation using tools like GitHub, IEX, and Confluence. - Continuously seek feedback to improve current and future projects. Qualifications Required: - 1-2 years of experience in a data analytics role for Bachelors/Masters graduates (preferably in Mathematics or a scientific discipline), or 2+ years in a comparable professional setting. - Intermediate proficiency in R, Python, or SQL for analyzing, structuring, and visualizing large datasets. - Basic understanding of probability, descriptive statistics, and frequentist concepts. - Strong business acumen with the ability to align analytics to strategic objectives. - Strong communication and influencing skills, tailoring insights to technical and non-technical audiences. - Demonstrated critical thinking and curiosity with a proactive, solutions-focused approach. (Note: Accommodation requests can be made if needed during the application process due to a disability or other conditions. Expedia Group has been recognized as a Best Place to Work on Glassdoor and for its award-winning culture by organizations like Forbes, TIME, Disability:IN, etc.) (Note: Expedia Group's family of brands includes Brand Expedia, Hotels.com, Vrbo, trivago, Orbitz, and others. Employment opportunities and job offers will always come directly from Expedia Group's Talent Acquisition and hiring teams, and sensitive information should only be provided to verified sources with @expediagroup.com domain.) Role Overview: You will be part of the Home team within the Product Analytics and Experimentation organization at Expedia Group. Your role will involve providing insights and measurement to support the Product team in making informed decisions about product features. You will work with stakeholders up to the Senior Manager level and apply analytical capabilities to solve business problems. Key Responsibilities: - Extract and integrate data from multiple sources for model building and analytics. - Design and recommend simple and complex experiments (e.g., A/B, pre/post, causal impact) to address business questions. - Build basic models (e.g., linear, logistic, clustering) and select appropriate data structures and formats. - Develop and maintain basic data pipelines and workflows to support modeling tasks. - Collaborate with stakeholders to refine project scope and requirements. - Apply business knowledge to shape modeling questions, select features, and guide decisions. - Deliver clear data stories and visualizations to support decision-making. - Automate recurring reporting and dashboarding tasks across multiple platforms. - Share documentation, code, and project artifacts with relevant audiences. - Communicate project goals, methods, insights to both technical and non-technical stakeholders. - Collaborate with analytics peers through brainstorming, peer review, and knowledge sharing. - Train stakeholders to use dashboards and self-service tools and promote data literacy. - Troubleshoot and resolve data issues to ensure efficient query and pipeline performance. - Uphold best practices for code sharing and documentation using tools like GitHub, IEX, and Confluence. - Continuously seek feedback to improve current and future projects. Qualifications Required: - 1-2 years of experience in a data analytics role for Bachelors/Masters graduates (preferably in Mathematics or a scientif

As an experienced QA ERP Consultant specializing in Oracle Cloud (Financials), you will play a crucial role in ensuring high-quality Oracle Cloud deployments. Your responsibilities will include: Role Overview: At Opkey, we empower enterprises to optimize their ERP investments with AI-powered automation. You will be responsible for executing functional, integration, and regression testing for Oracle ERP Cloud (Financials) modules. Your role will involve validating financial configurations, testing end-to-end workflows, creating and maintaining test cases, and collaborating with various teams to ensure successful Oracle Cloud implementations. Key Responsibilities: - Execute functional, integration, and regression testing for Oracle ERP Cloud (Financials). - Validate financial configurations and end-to-end workflows across GL, AP, AR, Cash Management, Fixed Assets, and Reporting. - Create, execute, and maintain test cases and scenarios for Financial modules. - Work on automation scenarios using AI-powered or no-code test automation platforms. - Collaborate with implementation partners to validate setups, financial flows, and business processes. - Document test cases, test evidence, results, and module-specific testing standards. Qualifications Required: - 3-5 years of hands-on experience in Oracle ERP Cloud (Financials). - Experience testing 2 or more modules: GL, AP, AR, CM, FA, Expenses, Revenue, Reporting. - Strong QA foundation with experience in both manual and automation testing. - Solid understanding of financial processes like period-end close, reconciliations, and accounting flows. - Good analytical, troubleshooting, and communication skills. Additional Company Details: At Opkey, you will have the opportunity to work with cutting-edge SaaS + AI automation technologies in a collaborative and innovation-driven culture. You will be part of a flexible work environment with competitive compensation, influencing quality standards for global ERP programs. Please note the bonus points if you have exposure to test automation tools, familiarity with AI/ML-driven testing capabilities, knowledge of APIs, FBDI, integrations, or third-party apps, and Oracle ERP Cloud certification(s).,

Role Overview: As a Teaching Assistant for the Data Science and Data Analyst Offline Programs, you will be a crucial support system for learners as they progress from foundational analytics to cutting-edge technologies such as Deep Learning, Natural Language Processing (NLP), and Generative AI. Your role will involve conducting doubt-clearing sessions, guiding hands-on activities, assisting in project development, and creating an engaging and application-driven learning environment in collaboration with instructors. Key Responsibilities: - Conduct regular doubt-clearing sessions covering core topics such as Python, statistics, SQL, Excel, data visualization, machine learning, deep learning, NLP, and generative AI. - Organize hands-on exercises, case studies, and model-building challenges using real-world datasets and tools like Pandas, Scikit-learn, Tensorflow, PyTorch, Hugging Face, and OpenAI APIs. - Monitor learner progress, identify conceptual gaps, and provide personalized support across foundational and advanced AI concepts. - Foster an engaging classroom environment by promoting curiosity, experimentation, and collaboration. Sub-Goals: - Strengthen learners" understanding in analytical and AI-driven topics through practice-oriented sessions. - Help students build confidence in solving complex problems using classical and modern AI tools. Outcome-Oriented Learning Facilitation: - Collaborate with instructors to assist learners in achieving key milestones such as Exploratory Data Analysis, Dashboard Design, Machine Learning Projects, NLP Pipelines, and Generative AI Capstone Projects. - Review and provide feedback on assignments involving regression, classification, neural networks, transformers, chatbot building, and generative model applications. - Guide learners in developing a diverse portfolio showcasing skills in data analysis, business problem-solving, and AI innovation. - Ensure students gain hands-on exposure to AI applications like image generation, language modeling, and real-time analytics. Sub-Goals: - Equip students with practical, in-demand skills for roles such as Data Analyst, Business Analyst, Data Scientist, and AI Engineer. - Bridge theoretical knowledge with practical implementation using industry-adopted tools and frameworks. Batch Management, Coordination, and Continuous Improvement: - Maintain batch records, track attendance, learner progress, and project completion. - Coordinate with academic and operation teams for seamless batch execution, including scheduling expert sessions on AI and managing resource distribution. - Resolve operational or technical issues hindering the learning process. - Collaborate in refining teaching methods and integrating feedback for improved delivery of advanced AI concepts. Sub-Goals: - Ensure smooth logistics and academic execution across beginner and advanced AI learning tracks. - Actively contribute to enhancing AI curriculum effectiveness and learner engagement strategies. Qualification Required: - Education: Bachelor's degree in Computer Science, Engineering, Statistics, or related field (or equivalent industry experience). - Technical Skills: Proficiency in Python, SQL, Excel, Statistics, data visualization, machine learning, deep learning frameworks, NLP libraries, and generative AI tools. - Hands-on Experience: Developing and deploying ML/DL models, building dashboards, NLP pipelines, and working with generative models. - Communication: Ability to explain fundamental and advanced AI concepts clearly and engagingly. - Mentorship: Passion for teaching and mentoring learners at various stages of their data and AI journey. - Collaboration & Time Management: Balancing academic guidance, operational tasks, and team collaboration effectively.,

As a Senior Consultant/Consultant Analytics at EY, you will have the opportunity to work with clients in the Banking and Insurance sectors to develop Analytics-Based Decision Making Frameworks. Your key responsibilities will include: - Developing Analytics Based Decision Making Frameworks for clients in the Banking and Insurance sector - Managing projects effectively - Building and maintaining relationships with clients - Supporting business development and new analytics solution development activities To succeed in this role, you will need: - Domain expertise in either Banking or Insurance industries - Proficiency in statistical modeling techniques such as Logistic/Linear regression, GLM modeling, Time-series forecasting, and Scorecard development - Hands-on experience with statistical tools like SAS, Python, and R - Familiarity with data visualization tools like Tableau and Qlikview - Experience in data mining techniques such as Clustering and Segmentation - Knowledge of machine learning and Python would be advantageous To qualify for this position, you should have: - A B Tech degree from a top-tier engineering school or a Masters in Statistics/Economics from a leading university - At least 6 years of relevant experience, with a minimum of 1 year of managerial experience for Senior Consultant, 1 year for Associate Consultant, and 3 years for Consultant roles Additionally, we look for candidates who possess: - Strong communication, facilitation, and relationship-building skills - Adaptability and creativity - Comfort working with senior executives - Strong leadership abilities At EY, we value collaborative individuals who can provide services across multiple client departments while meeting commercial and legal requirements. We are committed to creating an inclusive work environment and offer flexible working arrangements to help you balance your personal and professional priorities. EY is a global leader in assurance, tax, transaction, and advisory services, dedicated to building a better working world. We believe in providing our employees with the necessary training, opportunities, and creative freedom to excel. If you meet the criteria mentioned above and are passionate about making a difference, we encourage you to reach out to us at your earliest convenience. As a Senior Consultant/Consultant Analytics at EY, you will have the opportunity to work with clients in the Banking and Insurance sectors to develop Analytics-Based Decision Making Frameworks. Your key responsibilities will include: - Developing Analytics Based Decision Making Frameworks for clients in the Banking and Insurance sector - Managing projects effectively - Building and maintaining relationships with clients - Supporting business development and new analytics solution development activities To succeed in this role, you will need: - Domain expertise in either Banking or Insurance industries - Proficiency in statistical modeling techniques such as Logistic/Linear regression, GLM modeling, Time-series forecasting, and Scorecard development - Hands-on experience with statistical tools like SAS, Python, and R - Familiarity with data visualization tools like Tableau and Qlikview - Experience in data mining techniques such as Clustering and Segmentation - Knowledge of machine learning and Python would be advantageous To qualify for this position, you should have: - A B Tech degree from a top-tier engineering school or a Masters in Statistics/Economics from a leading university - At least 6 years of relevant experience, with a minimum of 1 year of managerial experience for Senior Consultant, 1 year for Associate Consultant, and 3 years for Consultant roles Additionally, we look for candidates who possess: - Strong communication, facilitation, and relationship-building skills - Adaptability and creativity - Comfort working with senior executives - Strong leadership abilities At EY, we value collaborative individuals who can provide services across multiple client departments while meeting commercial and legal requirements. We are committed to creating an inclusive work environment and offer flexible working arrangements to help you balance your personal and professional priorities. EY is a global leader in assurance, tax, transaction, and advisory services, dedicated to building a better working world. We believe in providing our employees with the necessary training, opportunities, and creative freedom to excel. If you meet the criteria mentioned above and are passionate about making a difference, we encourage you to reach out to us at your earliest convenience.

**Job Description:** As a candidate for this role, you will be responsible for advising on suitable statistical tests for academic research in various fields such as Engineering, Management, Life Sciences, or Social Sciences. You are expected to possess a strong conceptual understanding of the appropriate statistical tests based on the data type. Proficiency in SPSS is essential for conducting descriptive, inferential, and predictive analysis. Additionally, familiarity with time series analysis, econometrics, R, Stata, and AMOS will be advantageous. It is crucial that you can effectively interpret and communicate the findings/results of the statistical tests. Your expertise should cover tests like Factor Analysis, Chi-Square, Anova, Mancova, and Logistic Regression. **Qualifications Required:** - Graduation in BA/BCom/BSC - Post Graduation in MA/MCom/MSC **Additional Details:** ELK Education Consultants Pvt. Ltd. offers paid leaves as part of the benefits package. This role requires an ideal candidate with an M.Sc in Statistics who possesses a deep understanding of when to apply specific statistical tests and has hands-on experience with SPSS. Proficiency in MS Excel and STATA would be considered an added advantage. If you are keen on contributing your statistical expertise to academic research projects across multiple disciplines, this position at ELK Education Consultants Pvt. Ltd. could be the perfect fit for you. Total word count: 176 words.,

As a Valuation Analyst at Barclays, you will embark on a transformative journey to spearhead the evolution of the digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. Your role will involve leading and building automated forecasting solutions to evaluate acquisition marketing investments at the partner, channel, offer, and segment levels. Additionally, you will help drive marketing investment optimization decisions for the business, leveraging data science capabilities through operationalizing data platforms and advanced analytical methodologies and tools to forecast P&L and monitor model accuracy to drive the best outcomes across channels and partners. Key Responsibilities: - Proficient in Python, SAS, SQL. - Good knowledge of data analysis and statistical techniques (such as linear or nonlinear models, logistic regression, macroeconomic forecast, decision trees, cluster analysis, and neural networks, etc.). - Deep understanding of Cards P&L and forecasting methodologies. - Experience in Credit Card/Banking, Data Science, Machine Learning, and Advanced Analytics. - Experience with Data visualization. To be successful in this role, you may be assessed on key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology, as well as job-specific technical skills. This role is based in our Noida office. In your role as a Valuation Analyst, you will be responsible for extracting meaningful insights from complex data sets, developing robust decision models, and presenting actionable recommendations to stakeholders across departments. Qualifications Required: - Proficiency in Python, SAS, SQL. - Strong knowledge of data analysis and statistical techniques. - Deep understanding of Cards P&L and forecasting methodologies. - Experience in Credit Card/Banking, Data Science, Machine Learning, and Advanced Analytics. - Experience with Data visualization. As a Valuation Analyst at Barclays, you will have the opportunity to impact the work of related teams within the area, partner with other functions and business areas, and take responsibility for embedding new policies and procedures adopted due to risk mitigation. You will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as the Barclays Mindset to Empower, Challenge, and Drive.,