13 Arima Jobs nearby Mysore

As a Data Scientist, you will play a crucial role in utilizing your expertise in various tools and techniques to derive insights from data. Your primary responsibilities will include: - Utilizing Classification techniques such as Decision Trees and SVM, Distance metrics like Hamming, Euclidean, and Manhattan Distance, as well as Forecasting methods like Exponential Smoothing, ARIMA, and ARIMAX. - Implementing ML Frameworks including TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet for model development. - Conducting Statistical analysis and computing using tools like Python, PySpark, R, R Studio, SAS, and SPSS. - Applying Regression models like Linear and Logistic Regression, and conducting Hypothesis Testing using T-Test and Z-Test. - Familiarity with Probabilistic Graph Models and tools such as KubeFlow and BentoML. Qualifications required for this role include proficiency in the mentioned tools and techniques, along with a strong background in data analysis and machine learning. Additionally, experience with Langraph and Agentic AI would be beneficial. Kindly note that the Job Description does not include any additional details about the company.,

Role Overview: At o9 Solutions, we are looking for individuals who are eager to apply their expertise in machine learning techniques to contribute to our mission of digitally transforming planning and decision-making for enterprises. As part of our team, you will have the opportunity to work on cutting-edge AI-driven solutions that drive real value for our clients and the planet. Key Responsibilities: - Apply a variety of machine learning techniques such as clustering, regression, neural nets, and time series analysis to address real-world business challenges. - Develop and optimize models for demand sensing, forecasting, optimization, anomaly detection, simulation, and market intelligence. - Utilize the latest advancements in AI and ML to solve complex business problems effectively. - Collaborate with clients, project management, solution architects, consultants, and data engineers to ensure successful project delivery. Qualifications Required: - 4+ years of experience in time series forecasting using algorithms like exponential smoothing, ARIMA, and custom parameter tuning. - Experience in applied analytical methods in supply chain and planning domains. - Educational background in Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field. - Proficiency in Python and/or R for Data Science. - Deep knowledge of statistical and machine learning algorithms, scalable ML frameworks, and feature engineering. - Strong presentation and communication skills, with a focus on transparency and collaboration. Additional Details: o9 Solutions is a rapidly growing technology company with a strong entrepreneurial culture and a focus on making a significant impact in the industry. Our platform, the o9 Digital Brain, is at the forefront of digital transformations for leading global enterprises. We offer competitive salaries, stock options, and a supportive work environment that values diversity and work-life balance. Join us on our mission to drive innovation and change at scale. (Note: The company's expansion, valuation, and global presence are highlighted in the additional details section.),

As a Hardware Engineer at Qualcomm India Private Limited, you will play a crucial role in planning, designing, optimizing, verifying, and testing electronic systems. Your responsibilities will include working on various systems such as circuits, mechanical systems, Digital/Analog/RF/optical systems, equipment and packaging, test systems, FPGA, and/or DSP systems. You will be instrumental in launching cutting-edge products by collaborating with cross-functional teams to develop solutions and meet performance requirements. Key Responsibilities: - Design and implement end-to-end data analytics workflows tailored to semiconductor engineering use cases. - Develop, train, and optimize ML models using supervised, unsupervised, and deep learning techniques. - Perform feature engineering, model evaluation, and hyperparameter tuning to improve model performance. - Build scalable data ingestion and transformation pipelines using Python and cloud-native tools. - Apply statistical analysis and visualization techniques to derive insights from large datasets. - Conduct time series analysis using methods such as ANOVA and other statistical techniques. - Experiment with GenAI platforms, LLMs, and RAG techniques to enhance model capabilities. - Collaborate with cross-functional teams to integrate ML models into engineering workflows and tools. - Document methodologies and provide technical guidance to internal teams. Qualification Required: - Masters degree in Computer Science, Data Science, or a related field. - Strong programming skills in Python or C++. - Solid understanding of data structures, algorithms, and software design principles. - Strong analytical and problem-solving skills. - Hands-on experience with supervised and unsupervised learning techniques (e.g., classification, clustering, dimensionality reduction). - Experience with deep neural network architectures including RNNs, and Transformers. - Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. - Proficiency in data analysis using Pandas, NumPy, and Matplotlib. - Statistical Analysis & Visualization - Feature Engineering & Model Evaluation - Understanding of GPU, CUDA & High performance Computing Frameworks & Methods. Preferred Qualifications: - PHD in Computer Science, Data Science, or a related field. - Experience in large Model Development & Training from the Scratch. - Familiarity with time series analysis methods including ANOVA, ARIMA, and seasonal decomposition. - Familiarity with SQL databases, ETL frameworks, and cloud platforms (e.g., AWS). - Knowledge of LLM integration frameworks (e.g., LangChain). - Hands-on experience with distributed computing and cloud-scale data processing. - Software Design & Architecture Qualcomm India Private Limited is focused on applying state-of-the-art AI and ML technologies to enhance engineering efficiency through intelligent automation, data-driven insights, and innovative tool development. If you are a passionate and technically strong engineer looking to drive innovation in chip design, qualification, and debug engineering, this is the perfect opportunity for you.,

As a Senior Consultant, Data Scientist in the Supply Chain Consulting team at NTT DATA, you will play a crucial role in developing and deploying cutting-edge supply chain solutions for leading organizations. Your primary responsibility will be to design and implement time series forecasting models for demand planning and other supply chain use cases using both traditional statistical models and modern machine learning techniques. **Responsibilities:** - Design, develop, and implement time series forecasting models for demand planning and other supply chain use cases. - Apply statistical techniques such as ARIMA, ETS etc for effective & strong baseline modeling. - Implement and optimize machine learning algorithms (e.g., Boosting methods like LightGBM, CatBoost etc) to improve forecast accuracy. - Collaborate with clients to understand business problems and translate them into data science solutions. - Contribute to broader AI/ML initiatives across supply chain functions, including anomaly detection, inventory optimization, and scenario modeling. - Communicate results effectively to technical and non-technical stakeholders. - Work closely with digital supply chain platforms such as o9, Blue Yonder, or similar (experience preferred). **What You'll Bring:** - 5 to 8 years of hands-on experience in Data Science or Analytics, preferably in supply chain or operations domains. - Strong expertise in time series forecasting, with proven experience implementing models like ARIMA, ETS, etc. - Solid experience in applying machine learning techniques such as boosted trees, random forests, etc. - Proficiency in Python (including libraries like pandas, scikit-learn, statsmodels/StatsForecast/DARTS etc) and SQL. - Exposure to or experience with digital supply chain tools (e.g., o9, Blue Yonder) is highly desirable. - Strong problem-solving and communication skills with the ability to manage client interactions independently. - Understanding of MLOps, model deployment, or cloud platforms (Azure, AWS) is a plus. NTT DATA is a $30 billion trusted global innovator of business and technology services, serving 75% of the Fortune Global 100. They are committed to helping clients innovate, optimize, and transform for long-term success. With diverse experts in more than 50 countries and a robust partner ecosystem, NTT DATA provides services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. NTT DATA is a leading provider of digital and AI infrastructure worldwide and is part of the NTT Group, investing over $3.6 billion each year in R&D to support organizations and society in confidently transitioning into the digital future. Visit [NTT DATA](https://us.nttdata.com) for more information.,

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,

Qualcomm India Private Limited is looking for a Hardware Engineer to join their Engineering Group, specifically focusing on Hardware Engineering. As a Qualcomm Hardware Engineer, you will be responsible for planning, designing, optimizing, verifying, and testing electronic systems, circuits, mechanical systems, and equipment to launch cutting-edge products. You will collaborate with cross-functional teams to develop solutions and meet performance requirements. Key Responsibilities: - Design and implement end-to-end data analytics workflows tailored to semiconductor engineering use cases. - Develop, train, and optimize ML models using supervised, unsupervised, and deep learning techniques. - Perform feature engineering, model evaluation, and hyperparameter tuning to improve model performance. - Build scalable data ingestion and transformation pipelines using Python and cloud-native tools. - Apply statistical analysis and visualization techniques to derive insights from large datasets. - Conduct time series analysis using methods such as ANOVA and other statistical techniques. - Experiment with GenAI platforms, LLMs, and RAG techniques to enhance model capabilities. - Collaborate with cross-functional teams to integrate ML models into engineering workflows and tools. - Document methodologies and provide technical guidance to internal teams. Qualification Required: - Master's degree in Computer Science, Data Science, or a related field. - Strong programming skills in Python or C++. - Solid understanding of data structures, algorithms, and software design principles. - Strong analytical and problem-solving skills. - Hands-on experience with supervised and unsupervised learning techniques. - Experience with deep neural network architectures including RNNs and Transformers. - Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. - Proficiency in data analysis using Pandas, NumPy, and Matplotlib. - Familiarity with statistical analysis & visualization, feature engineering, and model evaluation. If you are a passionate engineer with a strong technical background, this role at Qualcomm offers the opportunity to work on advanced data analytics and machine learning models in the chip design, qualification, and debug engineering processes. You will play a key role in enhancing engineering efficiency through intelligent automation, data-driven insights, and innovative tool development.,

As a Data Scientist at mPokket, your role involves working with the data science team, planning projects, and building analytics models. You should possess a strong problem-solving ability and a knack for statistical analysis. Your main objective will be to align data products with business goals to enhance products and business decisions through effective data utilization. **Key Responsibilities:** - Overseeing the data scientists" team and data specialists. - Teaching, leading, and counseling colleagues on new techniques or solutions. - Collaborating with data and software engineers for deploying sciences and technologies across the company's ecosystem. - Conceiving, planning, and prioritizing data projects. - Building analytic systems and predictive models, while experimenting with new techniques. - Ensuring data projects align with organizational goals. **Qualifications Required:** - Master's degree in Computer Science, Operations Research, Econometrics, Statistics, or related technical field. - 2+ years of experience in solving analytical problems using quantitative approaches. - Proficiency in communicating quantitative analysis results. - Knowledge of relational databases and SQL. - Development experience in any scripting language (e.g., PHP, Python, Perl). - Familiarity with statistics (e.g., hypothesis testing, regressions). - Experience manipulating data sets through statistical software (e.g., R, SAS) or other methods. **Technical Skills - Must Have:** - Programming: Python (Preferred) / R. - ML Models: Regression (Linear, Logistic, Multinomial, Mixed effect), Classification (Random Forest, Decision tree, SVM), Clustering (K-Means, hierarchical, DB-Scan), Time series (ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS), Neural Networks (Deep learning), Naive Bayes, Excel, SQL. - Dimensionality Reduction: PCA, SVD, etc. - Optimization Techniques: Linear programming, Gradient Descent, Genetic Algorithm. - Cloud: Understanding of Azure / AWS offerings, setting up an ML pipeline in the cloud. **Good To Have:** - Visualization: Tableau / Power BI / Looker / QlikView. - Data Management: HDFS, Spark, Advanced Excel. - Agile Tools: Azure DevOps, JIRA, Pyspark, Big Data / Hive Database. - IDE: PyCharm. Please note that this job posting was by Debapti Roy from mPokket.,

As a Senior Consultant, Data Scientist in the Supply Chain Consulting team at NTT DATA, your role will involve designing and delivering cutting-edge supply chain solutions for leading organizations globally. Your primary focus will be on developing and deploying forecasting solutions using both traditional statistical models and modern machine learning techniques. Additionally, you will contribute to building AI/ML-driven solutions for various real-world supply chain challenges. **Responsibilities:** - Design, develop, and implement time series forecasting models for demand planning and other supply chain use cases. - Apply statistical techniques such as ARIMA, ETS, etc., for effective baseline modeling. - Implement and optimize machine learning algorithms (e.g., Boosting methods like LightGBM, CatBoost, etc.) to enhance forecast accuracy. - Collaborate with clients to comprehend business problems and translate them into data science solutions. - Contribute to broader AI/ML initiatives across supply chain functions, including anomaly detection, inventory optimization, and scenario modeling. - Communicate results effectively to technical and non-technical stakeholders. - Work closely with digital supply chain platforms such as o9, Blue Yonder, or similar (experience preferred). **What You'll Bring:** - 5 to 8 years of hands-on experience in Data Science or Analytics, preferably in supply chain or operations domains. - Strong expertise in time series forecasting, with proven experience in implementing models like ARIMA, ETS, etc. - Solid experience in applying machine learning techniques such as boosted trees, random forests, etc. - Proficiency in Python (including libraries like pandas, scikit-learn, statsmodels/StatsForecast/DARTS, etc.) and SQL. - Exposure to or experience with digital supply chain tools (e.g., o9, Blue Yonder) is highly desirable. - Strong problem-solving and communication skills with the ability to manage client interactions independently. - Understanding of MLOps, model deployment, or cloud platforms (Azure, AWS) is a plus. As part of NTT DATA, a trusted global innovator of business and technology services, we are committed to helping clients innovate, optimize, and transform for long-term success. With a diverse team of experts across more than 50 countries, we offer services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. Join us in shaping the digital and AI infrastructure of the future. Visit us at us.nttdata.com.,

As a Senior in the Tax Technology Transformation (TTT) team at EY, you will play a crucial role in developing, implementing, and integrating technology solutions to better serve clients and engagement teams. Your primary responsibilities will include: - Applying machine learning techniques to deliver actionable insights - Conducting end-to-end coding using Python and R - Developing models including data exploration, training data, feature extraction, and validation on both structured and unstructured data - Designing and building systems to mine massive datasets and apply AI/Machine Learning technology - Utilizing standard statistical methods, simulation models, and statistical programming - Collaborating with business users to define solutions and present results effectively - Acting as a subject matter expert on Machine Learning and Artificial Intelligence - Managing stakeholders and mentoring team members in AI/Machine Learning usage To qualify for this role, you must have: - A Masters degree in Statistics/Mathematics or a Bachelors/Masters degree in Science/Engineering/MCA - At least 4 years of overall experience with 2+ years of hands-on work experience in Machine Learning and Artificial Intelligence techniques - Expertise in software such as R, Python, and strong programming skills - Experience with end-to-end ML projects and tax applications Additionally, exposure to cloud platforms like Azure and AWS would be beneficial, along with strong verbal and written communication skills. At EY, you will have the opportunity to work with a diverse and inclusive culture, collaborate with a global team, and contribute to building a better working world. Continuous learning, transformative leadership, and a supportive environment are key pillars of EY's values.,

Role Overview: At o9 Solutions, you will be part of a mission to be the Most Valuable Platform (MVP) for enterprises by integrating global enterprises" planning capabilities through the AI-driven platform, the o9 Digital Brain. Your contribution will help businesses capture significant value leakage, reduce waste, and drive better outcomes for the planet. Join our team of bright and committed individuals to make a real difference for companies and the environment. Key Responsibilities: - Apply a variety of machine learning techniques such as clustering, regression, ensemble learning, neural nets, time series, and optimizations to leverage their real-world advantages and drawbacks. - Develop and optimize models for demand sensing/forecasting, optimization, anomaly detection, simulation, stochastic models, and market intelligence. - Utilize the latest advancements in AI/ML to solve business problems effectively. - Analyze complex problems by synthesizing information, evaluating alternate methods, and articulating results with relevant assumptions and reasons. - Implement common business metrics like Forecast Accuracy, Bias, MAPE, and generate new ones as required. - Develop or optimize modules to call web services for real-time integration with external systems. - Collaborate with Clients, Project Management, Solution Architects, Consultants, and Data Engineers to ensure successful delivery of o9 projects. Qualifications Required: - Experience: You should have 4+ years of experience in time series forecasting at scale using heuristic-based hierarchical best-fit models and algorithms like exponential smoothing, ARIMA, prophet, and custom parameter tuning. - Experience in applied analytical methods in the field of Supply Chain and planning, including demand planning, supply planning, market intelligence, and optimal assortments/pricing/inventory. - Educational Background: A Bachelor's Degree in Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field is required. - Languages: Proficiency in Python and/or R for Data Science is essential. - Skills: Deep knowledge of statistical and machine learning algorithms, building scalable ML frameworks, identifying and collecting relevant input data, feature engineering, tuning, and testing are necessary. - Characteristics: Independent thinking, strong presentation, and communication skills are valued. Additional Company Details: o9 Solutions is a rapidly growing technology company that aims to digitally transform planning and decision-making for enterprises and the planet. The culture at o9 is high-energy, driving the team to aim 10x in everything they do. The o9 Digital Brain, our premier AI-powered, cloud-native platform, is leading the digital transformations of major global enterprises like Google, Walmart, ABInBev, and Starbucks. Headquartered in Dallas, o9 Solutions has offices in various cities worldwide including Amsterdam, London, Bengaluru, Tokyo, Sydney, and more. (Note: The job description does not specify any details about the company beyond what is mentioned above.),

As a Data Scientist at our company, you will be responsible for leveraging your expertise in predictive modeling, time-series forecasting, and scenario analysis to drive data-driven decisions in the media and finance domains. Your role will involve a combination of advanced technical proficiency and the ability to translate analytical insights into strategic business outcomes. Key Responsibilities: - Design and implement forecasting and predictive models using statistical and machine learning techniques such as ARIMA, Prophet, XGBoost, and LSTM. - Build and validate scenario and what-if simulation models, applying explainable AI methods like SHAP and feature importance. - Develop end-to-end ML pipelines in Python/R/SQL, ensuring scalability and reproducibility through cloud ML platforms such as AWS SageMaker, Azure ML, Databricks, or GCP Vertex AI. - Collaborate with cross-functional teams to integrate forecasts into finance, content, and release planning workflows. - Communicate insights effectively to business stakeholders, influencing strategic and operational decisions. Qualifications Required: - 5-8 years of experience in time-series forecasting and predictive analytics. - Education background in BE - Computers or a Masters or higher degree in Data Science, Statistics, Applied Mathematics, Computer Science, or related field. - Proven hands-on proficiency in Python/R/SQL and major ML frameworks like Scikit-learn, TensorFlow, and PyTorch. - Familiarity with cloud-based ML environments and MLOps practices. - Strong business acumen, ideally within media, finance, or entertainment analytics. Location: Anywhere in India (Hyderabad, Bengaluru, Chennai, Mumbai, NCR) Note: Immediate candidates or those serving notice period are highly preferred for this position.,

Role Overview: You have an exciting opportunity to join the CO&D WKO Data Management team as a Statistical Data Analyst within the Commercial & Investment Bank. Your role involves utilizing statistical techniques to deliver actionable insights and support data-driven decision-making. You will collaborate with business partners, data engineers, and other analysts to translate business questions into statistical problems and deliver clear, concise results. Key Responsibilities: - Apply statistical techniques such as regression, hypothesis testing, time series analysis, and clustering to analyze business data and uncover insights. - Calculate descriptive statistics including mean, median, mode, variance, standard deviation, and percentiles to summarize data characteristics. - Conduct inferential statistical analyses using hypothesis testing, confidence intervals, p-values, t-tests, chi-square tests, and ANOVA. - Utilize probability theory by working with probability distributions, Bayes theorem, and random variables to model uncertainty. - Perform regression analysis with linear, logistic, and multivariate models, including thorough model diagnostics. - Implement sampling methods such as simple random, stratified, and cluster sampling, and determine appropriate sample sizes. - Analyze time series data for trends, seasonality, and forecasting using ARIMA and related models. - Demonstrate proficiency in R, Python (NumPy, pandas, SciPy, statsmodels), SAS, SPSS, and Stata for statistical analysis. - Partner with business stakeholders to translate business questions into structured analyses and actionable recommendations. - Clean, organize, and validate data to ensure the accuracy and reliability of analytical results. - Develop dashboards and reports in Tableau for effective data visualization and business consumption, and use Python for advanced analytics and automation. Qualifications Required: - Bachelors or Masters degree in Statistics, Mathematics, Data Science, Economics or related field. - 6+ years of experience in data analytics, business intelligence, or a similar role. - Strong foundation in Statistics (hypothesis testing, probability, regression, experimental design, sampling methods). - Proficiency in SQL for data extraction and manipulation. - Ability to work with large, complex datasets and draw actionable insights. - Excellent problem-solving, logical thinking, and business acumen. - Strong communication skills to explain technical findings to non-technical stakeholders.,

As a Data Science Consultant with 4-7 years of experience, you will be joining a dynamic team and working on challenging data science projects that have a significant impact on client outcomes. Your expertise in Machine Learning and NLP/GenAI will be crucial in developing and implementing advanced machine learning models and GenAI solutions for client projects. You will also be responsible for data preprocessing, feature engineering, exploratory data analysis, and evaluating model performance using appropriate metrics. Key Responsibilities: - Develop and implement advanced machine learning models and GenAI based solutions in client projects. - Perform data preprocessing, feature engineering, and exploratory data analysis to extract meaningful insights from large datasets. - Evaluate model performance using appropriate metrics and refine models for improved accuracy and efficiency. - Have an understanding of NLP starting from transformers to the new generation LLMs. - Mentor junior team members. - Communicate results and insights effectively to both technical and non-technical stakeholders. Qualifications: - Bachelors or masters degree in computer science, Statistics, Mathematics, Data Science, Economics, or a related field. - Strong skills in Python, SQL, API development, code version control, and Docker. - In-depth knowledge of machine learning algorithms, statistical methods, and their application in client engagements. - Hands-on experience with time series forecasting models such as ARIMA, SARIMA, Exponential Smoothing, Prophet, LSTM, and others. - Some hands-on experience with Retriever Augmented Generations either in POC or client engagements. - Comfortable with at least one cloud provider between Azure, GCP, or AWS. - Ability to pick up new technology as it comes. - Strong analytical and problem-solving skills with attention to detail. - Excellent communication skills, with the ability to explain complex analytical concepts to non-technical audiences.,