3352 Data Scientist Jobs - Page 19

Job Description Data Scientist Gurugram - Hybrid Purpose of the Role To monitor & implement the right statistical methodology in our data processes for universe, sample and extrapolation setup, data deep dives and analysis using advanced statistical tool. The role is responsible for supporting the Panel Quality Lead in ensuring that we follow GfKs globally approved methodology to ensure the statistical quality of the data is maintained and rightly represents the regional market. Key Activities POS Universe estimation by distribution channel in the country of interest. Presentation of the results of the universe study, comparison to previous years’ results and definition of the required changes to extrapolation model based on the study conducted. Calculation of the impact from the proposed changes on the currently conducted panel study. Management and updates of the address database of all shops that constitute the retail universe by distribution channel. Target sample calculation based on the reporting requirements, and defining recruitment targets for the team responsible for recruitment, in order to fulfill target sample quota. Maintenance of the current sample status information by distribution channel in accordance with client reporting requirements. Analysis of the results of applied data corrections/modifications in each period after data processing for the period has been completed. Preparation of a report based on the checks and analysis highlighting the necessary changes to extrapolation matrices and/or standard compensations used in data production. Development and adaptation of data modelling approach for companies not cooperating with GfK. Ensuring data quality issues are investigated and appropriate actions on extrapolation and representation of sample is taken. Hands on experience in handling market data QC queries and issues for challenging markets and product groups in order to be able to resolve quality issues as part of client operations. Able to work with big data sets, running new tools and statistical programs to run data deep dive and analysis. Functional responsibilities: Own target setting and assessment in People@GfK Internal project management Analysis of current market situation and preparation of proposals for future panel development in countries/channels under responsibility. Up to date knowledge and compliance with Standardized Global Processes (SGP); knowledge and understanding of internal data processing software (Startrack), including new developments and bug fixes (via Release Notes), and its efficient use in day-to-day tasks. Skills required Advanced knowledge in MS Office, MS Excel, MS Access Advanced knowledge in Statistics, Sampling methodology, Data Analysis, Project Management Excellent language skills in English Preferred knowledge of Statistical Software like Python, Knime & R Database Management & Project Management Additional Information Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion

Experience Required: 4-7 years Education Qualification: BE/ B. Tech, MCA, MSc (Statistics), MBA from Recognized University Job Description We are looking for a Data Scientist to join our Data Science team. Data science drives all the products we develop. Our products are designed for small to mid-size financial institutions to help them create strategies based on data. The team is responsible for working on predictive model use cases and working closely with technical and functional stakeholders in an agile environment. Role & Responsibilities 3-6 years of relevant work experience in the Data Science/Analytics domain Work with the data scientists’ team, and data engineers. Take ownership of end-to-end data science projects, including problem formulation, data exploration, feature engineering, model development, validation, and deployment, ensuring high-quality deliverables that meet project objectives. Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques. Collaborate with data architects and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem. Responsible for the conception, planning, and prioritizing of data projects Provide support to inexperienced analysts with high-level expertise in an open-source language (e.g., R, Python, etc.) Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown) Utilize data visualization tools (Power BI) to deliver insights to stakeholders. Competencies and Technical Skills Degree holder in computer science or related discipline Proficiency in SQL and database querying for data extraction and manipulation. Proficiency in programming languages such as Python/R, and experience with data manipulation and analysis libraries (e.g., NumPy, pandas, scikit-learn). Familiarity with data visualization tools (e.g., Tableau, Power BI) and proficiency in presenting complex data visually. Solid understanding of experimental design, A/B testing, and statistical hypothesis testing. Proven hands-on experience with machine learning algorithms and parameter tuning, including Ensemble methods (Random Forest, XGBoost), Logistic Regression, Support Vector Machines (SVM), and clustering techniques (e.g., K-Means, DBSCAN). Familiarity with Generative AI concepts and AI Agents is a plus. Excellent verbal and written communication skills, with the ability to effectively convey complex concepts to both technical and non-technical stakeholders· Experience with Snowflake is not necessary but preferable.

The Data Scientist position in Ahmedabad requires a minimum of 2+ years of experience. As a Data Scientist, you will be responsible for developing, deploying, and implementing solutions for artificial intelligence and machine learning problems and business needs. Your role will involve working with cross-functional teams to collect requirements, analyze data, and create/deploy machine learning models. It is essential to stay updated with the latest advancements in AI/ML research and technologies to drive continuous innovation. Your job will involve a combination of technical implementation and effective communication, collaboration, and documentation to ensure successful project outcomes and knowledge sharing within the team. You should have advanced knowledge of predictive analytics and time series analysis, utilize data-driven insights for decision-making, expertise in NLP techniques, experience in fine-tuning open-source LLMs, proficiency in SQL and Python for building and deploying machine learning models, writing clean and concise code, and adopting methods of version control, continuous integration, and deployment for reliable code management. Your responsibilities will include coordinating with QA engineers for proper testing procedures, implementing automated testing frameworks for expanded test coverage and efficiency, and maintaining comprehensive documentation for all developed solutions and systems. You will also need to document development processes and workflows for future reference. In addition, you are expected to foster a teamwork environment that encourages knowledge sharing, collaboration, and continuous learning. You will guide and support junior developers, provide necessary feedback to help them grow professionally, and foster innovation and creativity within the team to successfully implement practical solutions for technical issues. The company offers a handsome salary, certifications, flexible timings, a 5-day working week, loyalty bonus, excellent referral bonus, maternity leaves and benefits, recognition and awards, and monthly team activities to create a positive work environment.,

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Responsibilities Analyze raw data: assessing quality, cleansing, structuring for downstream processing Design accurate and scalable prediction algorithms Collaborate with engineering team to bring analytical prototypes to production Generate actionable insights for business improvements Qualifications Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.) At least 1 - 2 years' of experience in quantitative analytics or data modeling Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms Fluency in a programming language (Python, C,C++, Java, SQL) Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)

Job Title: Data Scientist Location: Onsite – Bangalore Experience Required: 7+ Years Employment Type: Contract 6 months Joining Timeline: Immediate Joiner Job Summary: ALIQAN Technologies is hiring a seasoned Data Scientist with a strong background in AI/ML/LLM-based solutions. The ideal candidate will develop and deploy cutting-edge models, work on Retrieval-Augmented Generation (RAG), and manage production-grade pipelines using tools like Databricks, LangChain, LLaMA, and more. This is an excellent opportunity to build intelligent applications and collaborate with cross-functional teams to drive business value. Key Responsibilities: Build and implement AI/ML/LLM applications using Python, scripting, and robust pipelines. Develop and deploy RAG workflows using LangChain, LlamaIndex , and open-source LLMs (e.g., LLaMA). Work with vector databases such as pgvector (Postgres), Pinecone, Milvus, ChromaDB , etc. Utilize Databricks, MLflow, Delta Lake, Apache Spark for scalable data and ML ops. Enable text-to-SQL /prompt-to-SQL functionalities via LLMs for structured queries. Build and deploy backend APIs with Flask or FastAPI for AI service integration. Manage end-to-end ML/Ops lifecycle , including CI/CD, monitoring, and retraining. Collaborate across engineering, product, and design teams to ship real-world AI products. Support demos/POCs and effectively communicate findings to non-technical stakeholders. Required Skills & Experience: 6–8+ years hands-on experience in data science/ML/GenAI roles. Strong in Python (pandas, numpy) and scripting. Proven experience in Databricks , Apache Spark , and MLflow . Hands-on with LLaMA / open-source LLMs , prompt engineering, fine-tuning (LoRA, QLoRA, PEFT). Proficient in vector databases: pgvector, Milvus, Chroma, Pinecone , etc. Familiar with LangChain, LlamaIndex , Hugging Face , Transformers , scikit-learn . Backend development experience with Flask/FastAPI , and REST APIs. Comfortable with PostgreSQL , relational + vector search integration. Cloud proficiency (AWS, GCP, Azure), Docker, Kubernetes, and CI/CD tools. Deep understanding of MLOps/LLMOps and cost-efficient AI deployment. Preferred (Good to Have): Experience with quantization , LoRA , GPTQ , model compression . Familiarity with Knowledge Graphs , Neo4j , Autogen , LangGraph . Exposure to Redis Stack , Elasticsearch (with vector search) , or AWS Lambda . Prior work on multi-agent systems and AI orchestration frameworks. Job Type: Contractual / Temporary Contract length: 6 months Pay: Up to ₹160,000.00 per month Work Location: In person

As a Data Scientist at Setu, you will have the opportunity to be a part of a team that is revolutionizing the fintech landscape. Setu believes in empowering every company to become a fintech company by providing them with cutting-edge APIs. The Data Science team at Setu is dedicated to understanding the vast population of India and creating solutions for various fintech sectors such as personal lending, collections, PFM, and BBPS. In this role, you will have the unique opportunity to delve deep into the business objectives and technical architecture of multiple companies, leading to a customer-centric approach that fosters innovation and delights customers. The learning potential in this role is immense, with the chance to explore, experiment, and build critical, scalable, and high-value use cases. At Setu, innovation is not just a goal; it's a way of life. The team is constantly pushing boundaries and introducing groundbreaking methods to drive business growth, enhance customer experiences, and streamline operational processes. From computer vision to natural language processing and Generative AI, each day presents new challenges and opportunities for breakthroughs. To excel in this role, you will need a minimum of 2 years of experience in Data Science and Machine Learning. Strong knowledge in statistics, tree-based techniques, machine learning, inference, hypothesis testing, and optimizations is essential. Proficiency in Python programming, building Data Pipelines, feature engineering, pandas, sci-kit-learn, SQL, and familiarity with TensorFlow/PyTorch are also required. Experience with deep learning techniques and understanding of DevOps/MLOps will be a bonus. Setu offers a dynamic and inclusive work environment where you will have the opportunity to work closely with the founding team who built and scaled public infrastructure such as UPI, GST, and Aadhaar. The company is dedicated to your growth and provides various benefits such as access to a fully stocked library, tickets to conferences, learning sessions, and development allowance. Additionally, Setu offers comprehensive health insurance, access to mental health counselors, and a beautiful office space designed to foster creativity and collaboration. If you are passionate about making a tangible difference in the fintech landscape, Setu offers the perfect platform to contribute to financial inclusion and improve millions of lives. Join us in our audacious mission and obsession with craftsmanship in code as we work together to build infrastructure that directly impacts the lives of individuals across India.,

You will be responsible for conducting literature searches, managing citations, summarizing information, and applying process engineering knowledge in the field of chemical manufacturing and development. Your role will involve utilizing citation management tools to organize research references, synthesizing large amounts of information into clear and concise reports, and applying your deep understanding of chemical compounds, reactions, and processes. You will be working at Pragmetis Pharmaserve, a manufacturing and research company that specializes in producing customized chemicals and exporting them to the UK and the USA.,

Data scientist roles and responsibilities include: Data mining or extracting usable data from valuable data sources Using machine learning tools to select features, create and optimize classifiers Carrying out the preprocessing of structured and unstructured data Enhancing data collection procedures to include all relevant information for developing analytic systems Processing, cleansing, and validating the integrity of data to be used for analysis Analyzing large amounts of information to find patterns and solutions Developing prediction systems and machine learning algorithms Presenting results in a clear manner Propose solutions and strategies to tackle business challenges Collaborate with Business and IT teams Data Scientist SkillsYou need to master the skills required for data scientist jobs in various industries and organizations if you want to pursue a data scientist career. Let’s look at the must-have data scientist qualifications. Key skills needed to become a data scientist: Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage. Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies. Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests. Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques. Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description. Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Tableau that help to visually encode data Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience. Strong Software Engineering Background Hands-on experience with data science tools Problem-solving aptitude Analytical mind and great business sense Degree in Computer Science, Engineering or relevant field is preferred Proven Experience as Data Analyst or Data Scientist

Who We Are We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Today, over 300 banks, retailers, and fintechs worldwide use Sardine to stop identity fraud, payment fraud, account takeovers, and social engineering scams. We have raised $145M from world-class investors, including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures. Our Culture We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we maintain a remote-first work culture. #WorkFromAnywhere We hire talented, self-motivated individuals with extreme ownership and high growth orientation. We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule. Location: Mumbai, India (Remote) About The Role We’re looking for a data-driven professional to help us measure, understand, and improve the performance of our risk strategies. In this role, you’ll analyze complex datasets, design metrics, build dashboards, and collaborate closely with stakeholders across the business to drive decision-making and optimize outcomes. What You'll Be Doing Develop and track key metrics to evaluate the effectiveness of risk strategies and operational performance. Conduct deep-dive analyses to uncover insights that drive improved decision-making and reduce exposure to fraud. Build and experiment with ML models to identify fraudulent patterns and enhance fraud detection capabilities. Partner with engineers to ensure accurate and scalable data instrumentation. Build and maintain self-serve dashboards and reporting tools using modern BI platforms. Translate business needs into analytical approaches in collaboration with cross-functional teams (e.g. Engineering, Business, Operations). Contribute to the design and evaluation of risk mitigation initiatives, ensuring they align with broader business objectives. What You'll Bring 5+ years of experience in a data-focused role (analytics, data science, or similar), with a track record of high-impact work Strong SQL and Python skills Hands-on experience with BI tools like Tableau, Sigma, or Metabase Exposure to building ML models to address business challenges Background in the fraud, risk, or compliance domain is a strong plus Proven ability to perform exploratory data analysis and cohort analysis, and translate findings into clear recommendations Strong communication skills and comfort presenting insights to technical and non-technical stakeholders A bias toward action, strong critical thinking, and a pragmatic approach to problem-solving Compensation: INR 34,00,000 - 50,00,000 + Equity with tremendous upside potential + Attractive benefits The compensation offered for this role will depend on various factors, including the candidate's location, qualifications, work history, and interview performance, and may differ from the stated range. Benefits We Offer Generous compensation in cash and equity Early exercise for all options, including pre-vested Work from anywhere: Remote-first Culture Flexible paid time off, Year-end break, Self care days off Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific 4% matching in 401k / RRSP - US and Canada specific MacBook Pro delivered to your door One-time stipend to set up a home office — desk, chair, screen, etc. Monthly meal stipend Monthly social meet-up stipend Annual health and wellness stipend Annual Learning stipend Unlimited access to an expert financial advisory Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you. To learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our Applicant and Worker Privacy Notice .

Job Posting TitleSR. DATA SCIENTIST Band/Level5-2-C Education ExperienceBachelors Degree (High School +4 years) Employment Experience5-7 years At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. Job Overview Solves complex problems and help stakeholders make data- driven decisions by leveraging quantitative methods, such as machine learning. It often involves synthesizing large volume of information and extracting signals from data in a programmatic way. Roles & Responsibilities Key Responsibilities Design, train, and evaluate supervised & unsupervised models (regression, classification, clustering, uplift). Apply automated hyperparameter optimization (Optuna, HyperOpt) and interpretability techniques (SHAP, LIME). Perform deep exploratory data analysis (EDA) to uncover patterns & anomalies. Engineer predictive features from structured, semistructured, and unstructured data; manage feature stores (Feast). Ensure data quality through rigorous validation and automated checks. Build hierarchical, intermittent, and multiseasonal forecasts for thousands of SKUs. Implement traditional (ARIMA, ETS, Prophet) and deeplearning (RNN/LSTM, TemporalFusion Transformer) approaches. Reconcile forecasts across product/category hierarchies; quantify accuracy (MAPE, WAPE) and bias. Establish model tracking & registry (MLflow, SageMaker Model Registry). Develop CI/CD pipelines for automated retraining, validation, and deployment (Airflow, Kubeflow, GitHub Actions). Monitor data & concept drift; trigger retuning or rollback as needed. Design and analyze A/B tests, causal inference studies, and Bayesian experiments. Provide statisticallygrounded insights and recommendations to stakeholders. Translate business objectives into datadriven solutions; present findings to exec & nontech audiences. Mentor junior data scientists, review code/notebooks, and champion best practices. Desired Candidate Minimum Qualifications M.S. in Statistics (preferred) or related field such as Applied Mathematics, Computer Science, Data Science. 5+ years building and deploying ML models in production. Expertlevel proficiency in Python (Pandas, NumPy, SciPy, scikitlearn), SQL, and Git. Demonstrated success delivering largescale demandforecasting or timeseries solutions. Handson experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow) for model tracking and automated retraining. Solid grounding in statistical inference, hypothesis testing, and experimental design. Preferred / NicetoHave Experience in supplychain, retail, or manufacturing domains with highgranularity SKU data. Familiarity with distributed data frameworks (Spark, Dask) and cloud data warehouses (BigQuery, Snowflake). Knowledge of deeplearning libraries (PyTorch, TensorFlow) and probabilistic programming (PyMC, Stan). Strong datavisualization skills (Plotly, Dash, Tableau) for storytelling and insight communication. Competencies ABOUT TE CONNECTIVITY TE Connectivity plc (NYSETEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. Our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers, medical technology and more. With more than 85,000 employees, including 9,000 engineers, working alongside customers in approximately 130 countries, TE ensures that EVERY CONNECTION COUNTS. Learn more atwww.te.com and onLinkedIn , Facebook , WeChat, Instagram and X (formerly Twitter). WHAT TE CONNECTIVITY OFFERS: We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority! Competitive Salary Package Performance-Based Bonus Plans Health and Wellness Incentives Employee Stock Purchase Program Community Outreach Programs / Charity Events IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com . If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities. Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.

SKILLS AND COMPETENCIES Technical Skills: • Advanced proficiency in Python with expertise in data science libraries (NumPy, Pandas, scikit-learn) and deep learning frameworks (PyTorch, TensorFlow) • Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques • Experience with big data processing using Spark for large-scale data analytics • Version control and experiment tracking using Git and MLflow • Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing. • DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations. • LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management. • MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining. • Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems. • LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security. • General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP. • Experience in creating LLD for the provided architecture. • Experience working in microservices based architecture. Domain Expertise: • Strong mathematical foundation in statistics, probability, linear algebra, and optimization • Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation • Expertise in feature engineering, embedding optimization, and dimensionality reduction • Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing • Experience with RAG systems, vector databases, and semantic search implementation • Proficiency in LLM optimization techniques including quantization and knowledge distillation • Understanding of MLOps practices for model deployment and monitoring Professional Competencies: • Strong analytical thinking with ability to solve complex ML challenges • Excellent communication skills for presenting technical findings to diverse audiences • Experience translating business requirements into data science solutions • Project management skills for coordinating ML experiments and deployments • Strong collaboration abilities for working with cross-functional teams • Dedication to staying current with latest ML research and best practices • Ability to mentor and share knowledge with team members Primary Skill Set: Microservices LLM, Agentic AI Framework, Predictive modelling

Position Overview Here at ShyftLabs, we are searching for an experienced Data Scientist who can derive performance improvement and cost efficiency in our product through a deep understanding of the ML and infra system, and provide a data driven insight and scientific solution ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation, Job Responsibilities: Research, design, and develop innovative generative AI models and applications Collaborate with cross-functional teams to identify opportunities for AI-driven solutions Train and fine-tune AI models on large datasets to achieve optimal performance Optimize AI models for deployment in production environments Stay up-to-date with the latest advancements in AI and machine learning Collaborate with data scientists and engineers to ensure data quality and accessibility Design, implement, and optimize machine learning algorithms for tasks like classification, prediction, and clustering Develop and maintain robust AI infrastructure Document technical designs, decisions, and processes, and communicate progress and results to stakeholders Work with cross-functional teams to integrate AI/ML models into production-level applications Basic Qualifications: Master's degree in a quantitative discipline or equivalent 5+ years minimum professional experience Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets, and using statistics to arrive at a recommendation Excellent verbal and written communication skills, with the ability to present information and analysis results effectively Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company Statistics : must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models Machine Learning : must have a deep understanding of ML algorithms (i-e , deep learning, random forest, gradient boosted trees, k-means clustering, etc) and their development, validation, and evaluation Programming : experience with Python or other scripting languages and database language ( e-g , SQL) or data manipulation ( e-g , Pandas) We are proud to offer a competitive salary alongside a strong insurance package We pride ourselves on the growth of our employees, offering extensive learning and development resources, Show

Become part of our team! Team introduction Department of Data and Analytics has its hub at DTICI Bengaluru India catering to data and analytics requirements for Daimler Truck. we are 150+ strong team comprising of Data engineers, Data scientists, AI engineers and Analysts What makes the team/department special Highly energetic and young team that solves business problems that have the potential to define we build our trucks Good Communication & presentation skills. Strong Knowledge of Azure Components Azure Data Lake, Azure Data Factory, Azure SQL, Azure Databricks Master in Statistics/Machine Learning/Economics/ Big Data analytics (Full -Time) Strong experience in object-oriented programming using Python & PySpark Experience developing, training, and evaluating (supervised/unsupervised) machine learning models such as linear regression, Logistic regression, k-means, time series forecasting, Hypothesis testing (ANOVA, t-test, etc.), random forest, SVMs, Naive Bayes, gradient boosting, kNN, Deep learning algorithms like CNN, ANN and Reinforcement learning, Anomaly detection Familiar with statistical distributions, correlation analysis, descriptive statistics, ROC, F1-Score, etc. Proficiency in Python, Scikit-learn and ML libraries. Strong understanding of statistical modeling and data preprocessing. Should have had at least 2 to 3 use cases where the candidate would have gained the experience of end to end development of Data science solution and deployment Problem definition - white boarding Hypothesis building and testing and Exploratory data analysis Data engineering to curate data for model Training, testing, deployment and MLops Job Title: Data Scientist (Iterative Model Development Traditional ML) Job Summary: We are seeking a Data Scientist with expertise in building and optimizing traditional ML models, specifically within the automobile domain. The ideal candidate will have strong experience in classical ML algorithms, survival models, time series, statistical modelling, and deployment of predictive models. Experience with streaming data and telematics data solutions is highly desirable. Key Responsibilities: Work with Daimler s Businesses and Enabling Areas to support key business functions Contribute to storyboarding our results, support recommendations for an executive-level audience and produce leadership-quality deliverables Develop and optimize traditional ML models (regression, decision trees, SVM, XGBoost, etc.) with strong knowledge on Hypothesis testing. Perform feature engineering and dataset preprocessing for model training. Build scalable machine learning pipelines for real-world applications. Work on time series forecasting, anomaly detection, recommendation systems, etc. Optimize model performance using hyperparameter tuning and cross-validation. Deploy ML models into production using cloud and on-premises solutions. Collaborate with cross-functional teams to integrate ML models into business processes. Analyze and interpret telematics data to derive actionable insights. Develop solutions for streaming data processing and real-time analytics.

Position Overview: Here at ShyftLabs, we are looking for an experienced Data Scientist who can derive performance improvement and cost efficiency in our product through a deep understanding of the ML and infra system, and provide a data-driven insight and scientific solution. Job Responsibilities: Data Analysis and Research: Analyzing a large dataset with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could complete and improve a complex ML and bidding system. Simulation and Modelling: Validating and quantifying the efficiency and performance gain from hypotheses through rigorous simulation and modelling. Experimentation and Causal Inference: Developing a robust experiment design and metric framework, and providing reliable and unbiased insights for product and business decision making. Basic Qualifications: Masters degree in a quantitative discipline or equivalent. 3+ years minimum professional experience. Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets and using statistics to arrive at a recommendation. Excellent verbal and written communication skills, with the ability to present information and analysis results effectively. Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company. Statistics: Must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models. Machine Learning: Must have a deep understanding of ML algorithms (i.e., deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and their development, validation, and evaluation. Programming: Experience with Python, R, or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas).

2 About the position: Chevron invites applications for the role of Lead Data Scientist in India. This position is integral to designing and developing AI/ML models that significantly accelerate the delivery of business value. The successful candidate will be working with business stakeholders to prototype and deliver innovative data science applications that add value to Chevron s business. This position will provide broad exposure to the application of technology to enable business with many opportunities for growth and professional development for the candidate. Key Responsibilities: Combine expertise in mathematics, statistics, computer science, and domain knowledge to create AI/ML models to solve various Chevron business challenges Collaborate closely with the AI Technical Manager and GCC Petro-technical professionals and data engineers to integrate models into the business framework. Identify and frame opportunities to apply advanced analytics, modeling, and related technologies to data to help Chevron businesses gain insight and improve decision making, workflow, and automation. Understand and communicate the value of proposed opportunity with team members and other stakeholders. Identify needed data and appropriate technology to solve identified business challenges. Clean data and develop and test models. Establish the life cycle management process for models. Provide technical mentoring in modelling and analytics technologies, the specifics of the modelling process, and general consulting skills. Drive innovation in AI/ML to enhance Chevrons capabilities in data-driven decision-making. Aligns with team on shared goals and outcomes, recognizes others contributions, and work collaboratively & seek diverse perspectives. Takes actions to develop self and others beyond existing skillset. Encourages innovative ideas, adapts to change and changing technologies Understand and communicate data, insights, and model behaviours to stakeholders with varying levels of technical expertise. Required Qualifications: Minimum 5 years of experience in designing and developing AI/ML models and/or various optimization algorithms. 10- 15 years of experience Solid foundation in mathematics, probability, and statistics with demonstrated depth of knowledge and experience in advanced analytics and data science methodologies (e.g. supervised and unsupervised learning, statistics, data science model development) Proficiency in Python and working knowledge of cloud AI/ML services (Azure Machine Learning and Databricks preferred) Domain knowledge relevant to the energy sector and working knowledge of Oil and Gas value chain (e.g., upstream, midstream, or downstream) and associated business workflows. Proven ability to frame data science opportunities, leverage standard foundational tools and Azure services to perform exploratory data analysis (for purposes of data cleaning and discovery), visualize data, and identify actions to reach needed results. Ability to quickly assess current state and apply technical concepts across cross-functional business workflows. Experience with driving successful execution, deliverables, and accountabilities to meet quality and schedule goals. Ability to translate complex data into actionable insights that drive business value. Demonstrated ability to engage and establish collaborative relationships both inside and outside immediate workgroup at various organizational levels, across functional and geographic boundaries to achieve desired outcomes. Demonstrated ability to adjust behaviour based on feedback and provide feedback to others. Team-oriented mindset with effective communication skills and the ability to work collaboratively. Chevron participates in E-Verify in certain locations as required by law.

ABOUT US aioneers is a digital first supply chain management consulting firm, headquartered in Germany. We use state of the art cloud data technology and decades of supply chain consulting experience to deliver innovative decision intelligence solutions to our customers. YOUR ROLE AT AIONEERS As a Senior Data Scientist, you will be a pivotal member of the data science team within aioneers. You will be leading the solution implementation of data science work streams within our supply chain analytics projects. Often the projects involve solving complex supply chain problems like demand forecasting, multi-echelon inventory optimization, production scheduling, intelligent order fulfillment, rough cut capacity planning (RCCP) etc. You will also provide technical guidance and mentorship junior data scientists in the team. You will own development and implementation of end-to-end life cycle of machine learning solutions from data modelling, feature engineering, ML solution structuring to MLOps process implementation of automated model serving You will play the role of a technology architect to design efficient MLOps process for large scale model deployments and high frequency servings using Azure data and ML services You will provide thought leadership to solution architects and project managers to come up with effective solution architecture for client s problems You will be building heuristics, Operations research techniques based (like linear programming and discrete optimization) solutions to solve optimization problems in supply chain space You will also lead the data engineering work activities within the projects to create required data models with features stores for ML implementations and post processing activities to make the outputs consumable for business use cases YOUR PROFILE We are looking for someone with 5 to 8 years of relevant data science and machine learning experience in solving supply chain problems Data Science and Machine Learning Skills Understanding of statistical methods (e.g., regression, hypothesis testing) and optimization techniques like linear programming and mixed-integer programming for supply chain problems Proficiency in methods like ARIMA, SARIMAX, Prophet, or advanced techniques using neural networks (e.g., LSTMs, Temporal Fusion Transformer) Familiarity with supervised and unsupervised learning for classification (e.g., demand segmentation) and clustering (e.g., supplier categorization) Knowledge of CI/CD pipelines for ML, including retraining, deployment, and monitoring models using Azure DevOps or GitHub Actions Supply Chain Domain Knowledge: Seasoned expertise in demand forecasting using ML. Understanding the nuances of intermittent, erratic and lumpy demand patterns and how to solve them using ML techniques Knowledge of EOQ, reorder point models, safety stock modelling and inventory simulation techniques would be a plus Programming and Technical Skills Expertise in setting up end to end MLOps processes - model training, deployment, and tracking experiments Expertise in creating data pipelines for ETL processes and connecting supply chain data sources Proficiency in integrating ERP data from systems like SAP into Azure via connectors or APIs Deploying scalable ML models as APIs using AKS (Kubernetes) Expertise in handling large-scale supply chain datasets using Spark, Databricks, or Azure Synapse Advanced query skills in Azure SQL Database or Cosmos DB for real-time analytics Advanced proficiency in Python for ML modelling, data analysis, and libraries like Scikit-learn, PyTorch, TensorFlow Version control and automating deployments using Azure DevOps or GitHub Actions Ability to think through automation, pipeline design and other MLOps processes Conceptual and pragmatic knowledge of the concepts of data modelling, feature engineering, fine tuning machine learning models, statistical model validation Educational Background and Experience Engineering degree in computer science, informatics, data analytics and other relevant branches Affinity for new technologies and a drive for independent learning Affinity for an open feedback culture with flat hierarchies WHY AIONEERS At aioneers, we are building the next generation innovative solutions on supply chain technologies. What we can offer is a wonderful team culture, flexible work hours, respect for your ideas, open discussions / open door policies and attractive remuneration. Your results count and not the hours. You will have the chance to actively participate in the development and execution of innovative business strategies on an international scale. Apply for this job Apply for this job

SreeVia Ai Technologies is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Diverse Lynx is looking for Data Scientist with Python ,AI/ML to join our dynamic team and embark on a rewarding career journey Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Job Description: Who We Are: Saks Global is a combination of world-class luxury retailers, including Neiman Marcus, Bergdorf Goodman, Saks Fifth Avenue and Saks OFF 5TH, as well as a portfolio of prime U.S. real estate holdings and investments. Saks Global is deeply committed to helping luxury consumers discover the most sought-after established and emerging brands from around the world. Powered by data-driven technology and centered on the customer, Saks Global is on a mission to redefine the luxury shopping experience through highly personalized service, with greater opportunities for product discovery across all channels. Role Summary: Central to Saks customer-centric marketing strategy is our Customer DNA. The successful candidate will be a highly independent and business-savvy Senior Data Scientist to lead the development and execution of advanced analytics that drive measurable business impact. The ideal candidate will demonstrate strong ownership of projects, from framing business problems to delivering actionable recommendations. They will support Saks strategies through the delivery of best-of-breed campaign management, measurement of all-channel and cross banner marketing promotions, the extraction of key analytical insights and by providing customer centric recommendations spanning both store and e-commerce channels. The ability to think strategically about customer and business challenges and proactively propose solutions will be critical to their success. Forward thinking is the key to this role as new technologies and opportunities present themselves. Key Qualifications: 5+ years of demonstrated ability in a similar data scientist role Bachelor s degree in data science, computer science, statistics, economics, mathematics, or a similar quantitative field; Master s Degree preferred Comprehensive experience with ML and AI modeling, especially in product recommendation algorithms and NLP. Proven track record of teaming up with data engineers for large-scale ML tool production Proficient programming skills in relevant languages/tools (Python, SQL, Spark, Git & Github, AWS EMR, Airflow, AWS SageMaker, Dataiku, or similar platforms) Ability to apply the ML/AI modeling approaches/classes of algorithms to business problems e.g., regressions, Random Forest, GBM, Neural Networks, boosted trees, LDA, collaborative filtering, etc. Strong business acumen and knowledge of retail business and digital marketing Excellent communication skills and value in building solid relationships cross-functionally to capture business needs and translate them into actionable project plans to influence real-world marketing applications or decisions Role Description: Lead the strategic development of data-driven solutions within areas such as business forecasting, product analytics, and targeted marketing. This includes designing and implementing data pipelines, developing analytical frameworks, and creating models that directly influence business decisions Manage end-to-end data science projects, from defining objectives and scope, to delivering actionable insights and recommendations. Ensure clear communication of project status, findings, and implications to business stakeholders Contribute to Product DNA data project to support merchandising and buying decisions Conduct ad-hoc analyses using customer, merchandising, operational, and macroeconomic data to support various Saks initiatives and deliver actionable insights to different functional teams Develop and automate analytical processes for generating customer profiles, creating targeted campaign lists, and performing post-campaign evaluations. Ensure that insights are actionable and directly applicable to marketing and CRM strategies Team up with Data Architects, Data Engineers, MLops Engineers, and other company players to conceive and execute data pipelines crucial for our personalization objectives Stay informed on the latest industry trends and advancements in data science, machine learning, and AI, incorporating new techniques and technologies as appropriate Drive research and methodology development for machine learning use cases in product recommendation, customer journey optimization, and conversion enhancement. Gather business requirements for critical blind spots in business processes such as access to customer information, and design an application that is marketer-friendly but solves data gaps and consumes data science models for end-user applications Your Life and Career at Saks: Exposure to rewarding career advancement opportunities A culture that promotes a healthy, fulfilling work/life balance Benefits package for all eligible full-time employees (including medical, vision and dental). Thank you for your interest in Saks. We look forward to reviewing your application. Saks provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Saks complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Saks welcomes all applicants for this position. Should you be individually selected to participate in an assessment or selection process, accommodations are available upon request in relation to the materials or processes to be used. Saks.com is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Position: Data scientist with python (TK58FSI RM 3413) Key Capabilities: DATA ANALYSIS Python Modeling (core), Data Scientist OOPS Python scripting is Must Have The model is managed in Github , so working with Git is an expected skill Expertise in Dashboard development using streamlit is optional , expect some experience with frontend/GUI development Also need familiarity with file and data management ( pandas, json) Database experience (SQL like tools) OPTIONAL Job Category: Embedded HW_SW Job Type: Full Time Job Location: Pune Experience: 5 - 8 Years Notice period: Immediate

ZS Advanced Data Science - Associate ZS is a place where passion changes lives. As a management consulting and technology firm focused on transforming global healthcare and beyond, our most valuable asset is our people. Here youll work side-by-side with a powerful collective of thinkers and experts shaping solutions from start to finish. At ZS, we believe that making an impact demands a different approach; and thats why here your ideas elevate actions, and here youll have the freedom to define your own path and pursue cutting-edge work. We partner collaboratively with our clients to develop products that create value and deliver company results across critical areas of their business including portfolio strategy, customer insights, research and development, operational and technology transformation, marketing strategy and many more. If you dare to think differently, join us, and find a path where your passion can change lives. Our most valuable asset is our people . At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems the ones that comprise us as individuals, shape who we are and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. About Advanced Data Science (ADS): ZS Advanced Data Science group is focused on creating practical impact for clients across various industries such as Healthcare and Bio-Tech, Hi-Tech & Telecommunication, Financial Services and Travel through advanced analytics and emerging data sources. Emerging datasets include both unstructured datasets (for example, text, voice, image, etc.) and semi-structured datasets (for example, patient-level records). Advanced analytical techniques span a range of innovative machine learning, artificial intelligence, advanced statistics and optimization approaches. Being part of the ADS group at ZS will be an opportunity for you to work on cutting-edge solutions, utilizing new age data sources to shape innovations across multiple areas, for our clients and the broader ZS community. A key enabler of our services is leveraging data in delivering client solutions. The data available about customers is getting richer and the problems that our customers are trying to answer continue to evolve. In our endeavor to stay ahead in providing solutions to these evolving complex problems, ZS has set up an Advanced Data Science which has three major focus areas: • Research the evolving datasets and advanced analytical techniques to develop new offerings/solutions • Deliver client impact by collaboratively implementing these solutions • Provide thought leadership by developing the ZS Point of View in this space Data Science Associate Data Science Associate (DSA) design, develop and execute high-impact analytics solutions for large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions. Responsibilities: Develop advanced algorithms that solve problems of large dimensionality in a computationally efficient and statistically effective manner • Execute statistical and data mining techniques (e.g. hypothesis testing, machine learning and retrieval processes) on large data sets to identify trends, figures and other relevant information • Collaborate with clients and other ZS stakeholders to effectively integrate and communicate analysis findings • Contribute to the evaluation of emerging datasets and technologies that may contribute to our analytical platform • Evaluating emerging datasets and technologies that may contribute to our analytical platform • Owning the development of select assets/accelerators for efficient scaling of capability, with a focus on leveraging generative AI and deep learning methodologies. • Integrate engineering principles into data science workflows, optimizing algorithms for performance, scalability, and maintainability. • Collaborate with the engineering team to implement and deploy data science solutions into production, ensuring seamless integration with existing systems. • Utilize software engineering best practices for version control, code review, testing, and documentation to maintain high-quality, reliable, and reproducible data science workflows. Qualifications: Bachelor's or master's degree or PhD in Computer Science (or Statistics) from a premier institute, and strong academic performance with analytic and quantitative coursework is required. • 1-3 years of Data Science experience, including proficiency in generative AI, deep learning, statistical techniques, and engineering integration for scalable solutions. • Knowledge of programming (e.g. Java/Python/R); • Knowledge of big data/advanced analytics concepts and algorithms (e.g. text mining, social listening, recommender systems, predictive modeling, etc.); • Excellent oral and written communication skills. • Strong attention to detail, with a research-focused mindset; • Excellent critical thinking and problem-solving skills; • High motivation, good work ethic and maturity. • Exposure to Generative AI and its usage to solve problems is a plus. Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Considering applying? At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact in global healthcare and beyond. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To Complete Your Application: Candidates must possess work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At: www.zs.com

Job description: We are having a F2F weekend drive for the requirement of a Data Scientist + Gen AI at our LTIM Hyderabad office Date - 2nd August 2025 Experience - 6+ Years Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS, AI/ML, NLP Location - LTIMindtree - Hyderabad Office. Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment. Generic JD- More than 5 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen

Primary Responsibilities: Developing end-to-end pipeline for different document processing use cases Connecting with business for requirement gathering and status updates Maintaining accuracy of the work delivered Work closely with team lead throughout the solution development lifecycle, from design to implementation Work with the business teams to operationalize the ML solution for document processing solutions Engage in client communications for all important functions including requirement gatherings, strategizing solutions, delivering updates etc. Acquire understanding of US Healthcare domain Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Working understanding of deep learning especially NLP space Proficient in tools such as Python, SQL , Spark Microsoft Office Excel or PowerPoint Proficient in statistical techniques and standard Machine Learning Proficient in Generative AI and Agentic AI At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission. #NIC Apply Internal Employee Application

We are looking for an enthusiastic Data Scientist to join our team based in Bangalore. You will be pivotal in developing, deploying, and optimizing recommendation models that significantly enhance user experience and engagement. Your work will directly influence how customers interact with products, driving personalization and conversion. Responsibilities Model Development: Design, build, and fine-tune machine learning models focused on personalized recommendations to boost user engagement and retention. Data Analysis: Perform a comprehensive analysis of user behavior, interactions, and purchasing patterns to generate actionable insights. Algorithm Optimization: Continuously improve recommendation algorithms by experimenting with new techniques and leveraging state-of-the-art methodologies. Deployment and Monitoring: Deploy machine learning models into production environments, and develop tools for continuous performance monitoring and optimization. Requirements Education level: Bachelor's degree (B. E. / B. Tech) in Computer Science or equivalent from a reputed institute. Technical Expertise Strong foundation in Statistics, Probability, and core Machine Learning concepts. Hands-on experience developing recommendation algorithms, including collaborative filtering, content-based filtering, matrix factorization, or deep learning approaches. Proficiency in Python and associated libraries (NumPy, Pandas, Scikit-Learn, PySpark). Experience with TensorFlow or PyTorch frameworks and familiarity with recommendation system libraries (e. g., torch-rec). Solid understanding of Big Data technologies and tools (Hadoop, Spark, SQL). Familiarity with the full Data Science lifecycle from data collection and preprocessing to model deployment. This job was posted by Rituza Rani from Oneture Technologies.

Join us as a Data Scientist You’ll design and implement data science tools and methods which harness our data in order to drive market leading purposeful customer solutions We’ll look to you to actively participate in the data community to identify and deliver opportunities to support the bank’s strategic direction through better use of data This is an opportunity to promote data literacy education with business stakeholders supporting them to foster a data driven culture and to make a real impact with your work We're offering this role at associate level What you'll do As a Data Scientist, you’ll bring together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques and algorithms to develop and implement ethically sound models end-to-end. We’ll look to you to understand the needs of business stakeholders, form hypotheses and identify suitable data and analytics solutions to meet those needs in order to support the achievement of our business strategy. You’ll Also Be Using data translation skills to work closely with business stakeholders to define detailed business questions, problems or opportunities which can be supported through analytics Applying a software engineering and product development lens to business problems, creating, scaling and deploying software driven products and services Working in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and scrum outcomes Selecting, building, training and testing machine learning models considering model valuation, model risk, governance and ethics, making sure that models are ready to implement and scale Iteratively building and prototyping data analysis pipelines to provide insights that will ultimately lead to production deployment The skills you'll need You’ll need a strong academic background in a STEM discipline such as Mathematics, Physics, Engineering or Computer Science. You’ll have atlease four years of experience with statistical modelling and machine learning techniques. We’ll also look for financial services knowledge, and an ability to identify wider business impact, risk or opportunities and make connections across key outputs and processes You’ll Also Demonstrate The ability to use data to solve business problems from hypotheses through to resolution Experience indata science, analytics, and machine learningwith strong understanding of statistical analysis, machine learning models and concepts, LLMs, and data management principles Proficiency in Python and relevant libraries such as Pandas, NumPy, and Scikit-learn Experience of cloud applications such as AWS Sagemaker and data visualisation tools Experience in synthesising, translating and visualising data and insights for key stakeholders Good communication skills with the ability to proactively engage with a wide range of stakeholders