2382 Data Science Jobs

We are looking for a highly motivated and skilled Data Scientist with 5 years of experience. The ideal candidate should be proficient in Python, ML frameworks, and statistical modeling. You will develop machine learning models, analyze large structured and unstructured datasets, and provide actionable insights to drive business decisions. The role requires strong analytical thinking, effective communication, and hands-on experience with modern data science tools and libraries. You'll work closely with cross-functional teams, enabling data-driven strategies that impact core business outcomes.

Design & Develop intelligent Agentic AI agents that revolutionize industry * Design, develop & deploy AI solutions using Python, ML algorithms & React Native/JS * Collaborate with cross-functional teams on data science projects

About the Role Love deep data? Love discussing solutions instead of problems? Then you could be our next Data Scientist. In a nutshell, your primary responsibility will be enhancing the productivity and utilization of the generated data. Other things you will do are: Work closely with the business stakeholders Transform scattered pieces of information into valuable data Share and present your valuable insights with peers What You Will Do Develop models and run experiments to infer insights from hard data Improve our product usability and identify new growth opportunities Understand reseller preferences to provide them with the most relevant products Designing discount programs to help our resellers sell more Help resellers better recognize end-customer preferences to improve their revenue Use data to identify bottlenecks that will help our suppliers meet their SLA requirements Model seasonal demand to predict key organizational metrics Mentor junior data scientists in the team What You Will Need Bachelor's/Master's degree in computer science (or similar degrees) 2-4 years of experience as a Data Scientist in a fast-paced organization, preferably B2C Familiarity with Neural Networks, Machine Learning, etc. Familiarity with tools like SQL, R, Python, etc. Strong understanding of Statistics and Linear Algebra Strong understanding of hypothesis/model testing and ability to identify common model testing errors Experience designing and running A/B tests and drawing insights from them Proficiency in machine learning algorithms Excellent analytical skills to fetch data from reliable sources to generate accurate insights Experience in tech and product teams is a plus Bonus points for: Experience in working on personalization or other ML problems Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshift, etc.

Key Responsibilities Design and develop machine learning models for computer vision tasks including object detection, classification, tracking, and scene understanding. Lead end-to-end model lifecycle: data preprocessing, feature engineering, model selection, training, evaluation, and deployment. Implement and experiment with state-of-the-art techniques including Vision Transformers (ViT) and class-incremental learning for continuous adaptation in production environments. Analyze data from edge devices and physical environments to generate actionable insights. Develop and maintain reproducible research pipelines using versioned data and experiment tracking tools. Collaborate with the ML Ops and engineering teams to ensure seamless integration of models into production environments. Optimize models for real-time inference performance, accuracy, and scalability on edge devices or cloud-based infrastructure. Document findings, present insights to cross-functional teams, and contribute to technical decision-making. Mentor junior data scientists and contribute to team knowledge sharing. Required Qualifications 4+ years of experience in data science or machine learning roles, with hands-on production experience. Expertise in computer vision algorithms and deep learning models.\ Strong grasp of cutting-edge architectures such as CNNs , Vision Transformers (ViT) , and knowledge distillation techniques. Practical experience with class-incremental learning , transfer learning , and domain adaptation . Proficiency in Python and ML libraries such as PyTorch , TensorFlow , scikit-learn , and OpenCV . Hands-on experience with data versioning and experiment tracking tools such as DVC , MLflow etc. Solid understanding of ML model deployment and lifecycle management. Strong experience in working with structured and unstructured data, especially large-scale image/video datasets. Excellent analytical skills and the ability to interpret complex data and communicate results clearly. Preferred Qualifications Prior experience in startup or high-growth environments where adaptability is key. Experience working with cloud platforms such as AWS , GCP , or Azure for scalable ML workflows. Familiarity with edge computing , real-time inference , and model optimization frameworks like TensorRT , ONNX , or OpenVINO . Experience with CI/CD pipelines for ML projects and collaboration with ML Ops teams. Domain knowledge in retail, healthcare, logistics, or behavioral analytics is a strong plus. Contributions to open-source ML projects or published research papers. Comfort with visualization tools and reporting frameworks for data storytelling.

Experience: 2 + years Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Office (Pune) Placement Type: Full Time Permanent position Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost As an ML / Data Science Engineer at Anervea, youll work on designing, training, deploying, and maintaining machine learning models across multiple products. Youll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. Youll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomesnot just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions

Experience: 15 + years Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Hybrid (Bengaluru) Placement Type: Full time Permanent Position Must have skills required: Product Management, payment, Platform The Associate Director, Product Management will serve as the key internal product expert of Payments technology bringing deep prior experience from Payments and FinTech industries. You will drive prioritization and guide key trade-off and sequencing decisions balancing effectively for value, adoption, and scale. This leader is highly-visible with audiences from the C-Suite down. This leader will also be responsible for people management of 6+ PMs based in Bangalore, dedicated to delivering outcomes across our Purchase domains. A strong candidate is an adept strategic thinker and product operator, with proven success acting with pragmatism and hands-on involvement delivering results with their teams. Responsibilities: Partner with senior leaders to define and align the business and product vision for payments at Wayfair Deliver measurable impact (e.g., improving authorization rates and reducing costs) across core payments systems including authorization, settlement, routing, and tokenization Lead, develop, and mentor a team of 6+ Bangalore-based product managers, fostering a high-performance, customer-obsessed product culture Partner deeply with Engineering and Data Science to build a resilient, scalable, and secure payments infrastructure supporting multiple programs and lines of business Shape technology strategy and product roadmaps with Wayfairs 20+ global external payments vendors and partners streamlining working models, processes, and solutions Lead cross-functional teams in roadmapping, prioritization, and product delivery across key domains, including Cart & Checkout, Loyalty, Financing, Payments, Fraud, and Gift Cards Drive collaboration across internal stakeholders while incorporating external industry insights to shape investment decisions and surface opportunities for innovation Act as a key voice for Payments, providing senior stakeholders with clear, data-backed perspectives on priorities, trade-offs, and product value Regularly monitor performance of initiatives and communicate performance metrics to key stakeholders Leverage data to understand risks, impacts, scope and priorities of our business objectives, and enable the teams to drive results Establish operating models and decision frameworks that accelerate execution and increase cross-functional alignment Qualifications: 15+ years of experience in product management, including significant work in Payments or FinTech at scale (UX and Platforms, strong record of success) Proven people leadership experience with a track record of coaching, mentoring, and building high-performing product teams of 6+ PMs, particularly in distributed settings Deep domain expertise in the Payments ecosystem, with strong hands-on understanding of authorization, routing, tokenization, and related systems Proven tenure building and shaping external vendor partnerships Excellent analytical and problem-solving skills, with experience in hypothesis-driven thinking and converting data into actionable insights Strong strategic instincts and the ability to balance long-term platform investments with immediate business needs Excellent communication and stakeholder management skills, with the ability to influence across domains and at all levels of the organization Sufficient technical fluency to engage in architecture, infrastructure, and system design decisions. Able to extract and guide the necessary trade-off decisions as needed between value, scalability, and time horizon

We are seeking an experienced GCP MLOps Engineer with a strong background in Data Science and Analytics. The ideal candidate will have at least 5 years of experience working with Google Cloud Platform (GCP), Python, Vertex AI, SQL, and other relevant technologies. This role requires a blend of technical proficiency, analytical skills, and the ability to work collaboratively within a team.

Required Qualifications - B/Tech or M/Tech in Computer Science/ Data Science from a reputed educational institute. - 5 to 8 years of proven relevant experience in data architecture & AI/ML working for a good MNC company. - Work experience/Knowledge of the healthcare domain is highly desirable Apply machine learning, deep learning & Gen AI tools, focusing on doing feasibility studies, developing proof of concept implementaons, and establishing robust soluon blueprint for subsequent implementaon by Engineering teams. - Keep track of the latest emerging technologies, idenfy data trends, and perform complex data analysis and analycs using AI /ML & Gen AI. - Use Generave AI (GEN-AI), predicve and prescripve analycs to generate innovave ideas and soluons. - Yoke NLP and computer vision techniques to extract insights from unstructured clinical/healthcare data. - Apply core data modeling, data engineering principles and pracces, leveraging large datasets to design AI powered soluons. - Perform data analysis and data visualizaon to deliver data-driven insights. - Develop architecture blueprints, strategies for building robust AI powered soluons leveraging large datasets. - Define best pracces, pracces, standards for developing and deploying AI models to producon environments using MLOps. - Providing technical guidance and support to Data Engineers, Business users, and soware applicaon team members - Maintaining documentaon and ensuring compliance with relevant AI governance, regulaons, and standards. - Communicate effecvely with both technical and non-technical stakeholders. - Collaborate with cross-funconal teams, including business stakeholders, data sciensts, data engineers, and IT teams, to define future data management architecture, aligning with value creaon opportunies across the business. Competencies: - Good understanding of strategic and emerging technology trends and the praccal applicaon of exisng and emerging technologies to new and evolving business and operang models, especially AI/ML, GEN AI. - Ability to develop architecture blueprints, strategies. - Ability to effecvely communicate and present to senior-level execuves and technical audiences. - Proficiency in architecng soluons using Cloud Nave approach. - Well versed with Data modelling techniques and tools (Star Schema (de-normalized data model), Transaconal Model (Normalized data model) - Proven skills in building data systems that are reliable, fault tolerant, performing and at the same me equally economical from a cost perspecve. - Listens to the ideas, concerns of stakeholders, and develops an understanding of how their ideas relate to others - and acts to address concerns. - Idenfies risks and develops risk management plans/processes and successfully implements/operates them. - Possess a deep personal movaon to develop new efficient, effecve, and valuable ways to accomplish team tasks. - Demonstrates crical\out of box thinking and the ability to look at problems from different points of view and tries to find soluons that meet the needs of those outside of the team including staff and members. - Proacvely experiments with new digital technologies and be a technology evangelist sharing the key learning with colleagues.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/ Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Role Synopsis This role is a senior-level position within a data science team, responsible for providing leadership, strategic direction, and technical expertise in the field of data science and machine learning. This role involves leading all aspects of and guiding a team of data scientists while collaborating closely with multi functional departments, such as engineering, product management, and business collaborators. The Lead Data Scientist plays a pivotal role in crafting data-driven strategies and solutions that chip in to the organization's success and growth Key Accountabilities Data Analysis and Modeling: Lead data scientists must have a confirmed foundation in data analysis and a deep understanding of various machine learning algorithms They should be able to apply these techniques to address sophisticated problems and extract valuable insights from data Out of Code computing: Use libraries that support out-of-core computing, such as Dask in Python These libraries can process data that doesn't fit into memory by reading it in smaller portions from disk Business Insight: Understanding the FDO's business objectives and aligning data initiatives with them Project Management: Being skilled in project management methodologies helps in planning and driving data science projects efficiently Machine Learning: Innovation and Strategy - Advanced Machine Learning Skills for complex models. Evaluation Collaboration and Communication: Effective communication with collaborators, Explain the modeling approach and results. Implement to privacy guidelines and recommendation with conscious balance Continuous Learning: Staying up-to-date in competitive edge. Apply methodologies to practical business challenges. Meeting with domain GPO's Data cleaning and preprocessing, analysis: The ability to clean and preprocess data effectively is a fundamental skill in any data science role Data Ethics and Privacy: Open communication with customer. Ethical considerations in algorithm design. Secure data handling, Data minimization Database Management: Proficient in database systems and SQL is required for data retrieval and storage Domain knowledge: Expertise in the domain they are working in to understand the context and requirements of the data projects better Statistical Analysis and Mathematics: Solid grasp of statistical methods and mathematical concepts is needed for data analysis, modeling, and drawing substantial insights from data Experience and Job Requirements Data Science Team plays a crucial role in driving data-informed decision-making and generating actionable insights to support the company's goals. This team is responsible for processing, analyzing, and interpreting large and complex datasets from multiple datasets to provide valuable insights and recommendations across various domains. Through advanced analytical techniques and machine learning models, the data science team helps optimize processes, predict trends, and build data-driven strategies. A bachelor's or equivalent experience or master's degree in quantitative, qualitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related data field is often required Skills: Leadership role in Data Analysis, Programming proficiency in Python, SQL, Azure Databricks, Statistics & Mathematics. Leadership qualities to steer the team. Strategic direction and technical expertise Soft skills: Active listening, Translate business problems into data questions, Communication and collaboration, Presentation, Problem solving, Multi-functional, Team management, Partner management Data Sources: SAP, Concur, Salesforce, Workday, Excel files Other: Project management. Domain knowledge [Procurement, Finance, Customer], Business Insight, Critical thinking, Story telling Able to prepare analytical reports, presentations and/or visualisation dashboards to communicate findings, important metrics and insights to both technical and non-technical customers Stay up to date with industry trends, standard methodologies and new technologies in data analytics, machine learning, data science techniques.

NYU Manager - Owais UR Delivery Manager - Laxmi Title: Senior Data Developer with Strong MS/Oracle SQL, Python Skills and Critical Thinking Description: The EDA team seeks a dedicated and detail-oriented Senior Developer I to join our dynamic team. The responsibility of the successful candidate will be to handle repetitive technical tasks, such as Healthy Planet MS SQL file loads into a data warehouse, monitor Airflow DAGs, manage alerts, and rerun failed processes. Additionally, the role will require the analyst to monitor various daily and weekly jobs, which may include generation of revenue cycle reports and data delivery to external vendors. The perfect candidate will have a robust experience with MS/Oracle SQL, Python, Epic Health Systems, and other relevant technologies. Overview: As a Senior Developer I at NYU EDA team, you will play a vital role to improve the operation of our data load and management processes. Your primary responsibilities will be to ensure the accuracy and timeliness of data loads, maintain the health of data pipelines, and monitor that all scheduled jobs are completed successfully. You will collaborate with cross-functional teams to identify and resolve issues, improve processes, and maintain a high standard of data integrity. Responsibilities: Manage and perform Healthy Planet file loads into a data warehouse. Monitor Airflow DAGs for successful completion, manage alerts, and rerun failed tasks as necessary. Monitor and oversee other daily and weekly jobs, including FGP cash reports and external reports. Collaborate with the data engineering team to streamline data processing workflows. Develop automation scripts to reduce manual intervention in repetitive tasks using SQL and Python. Ensure all data-related tasks are performed accurately and on time. Investigate and resolve data discrepancies and processing issues. Prepare and maintain documentation for processes and workflows. Conduct periodic data audits to ensure data integrity and compliance with defined standards. Skillset Requirements: MS/Oracle SQL Python Data warehousing and ETL processes Monitoring tools such as Apache Airflow Data quality and integrity assurance Strong analytical and problem-solving abilities Excellent written and verbal communication Additional Skillset Familiarity with monitoring and managing Apache Airflow DAGs. Experience: Minimum of 5 years experience in a similar role, with a focus on data management and process automation. Proven track record of successfully managing complex data processes and meeting deadlines. Education: Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. Certifications: Epic Cogito MS/Oracle SQL, Python, or data management are a plus.

We are looking for an experienced Statistical Analytics Engineer to drive data-driven innovation in chemistry and materials science. You will apply statistical, AI, and data science techniques to develop and optimize data solutions that support smarter decision-making and workflow automation. The ideal candidate will lead analytics projects, operationalize data pipelines, and work on cross-functional initiatives. A strong foundation in cheminformatics, materials informatics, and interactive app development is essential. You will also support teams in adopting data tools, ensure data quality, and contribute to continuous learning and internal knowledge sharing.

Data Scientist 2-Digital Banking Kotak 811-Regional Sales Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Role & responsibilities You should be someone who thrives on solving complex problems and has a natural attraction to ill-defined challenges that seem intractable, transforming them into elegant data science solutions. You find yourself comfortable in the middle of what seems to be chaos, knowing you can discover patterns and create order through data. You want to create a meaningful impact by solving complex healthcare problems through your passion for data science and machine learning. Advanced degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field 5+ years of hands-on data science experience with a proven track record of deploying ML models to production Expert-level proficiency in SQL and Python , with extensive experience using standard Python machine learning libraries (scikit-learn, pandas, numpy, matplotlib, seaborn, etc.) Cloud platform experience, preferably AWS, with hands-on knowledge of SageMaker, S3, Redshift, and Jupyter Notebook workbenches (other cloud environments acceptable) Strong statistical modeling and machine learning expertise across supervised and unsupervised learning techniques Experience with model deployment, monitoring, and MLOps practices Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders Preferred candidate profile

The Data Scientist-3 in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk, Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are deployed for real time or near real time consumption and integrated into our proprietary Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the growth trajectory of a super fast evolving digital product. Key Requirements of The Role Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 7 - 10 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product and business teams Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets. Strong experience in NLP, time series forecasting and recommendation engines preferred Create great data stories with expertise in robust EDA and statistical inference. Should have at least a foundational understanding in Experimentation design ? Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch, Caffe preferred Experience with analytical programming languages, tools and libraries (Python a must) as well as Shell scripting. Should be proficient in developing production ready code as per best practices. Experience in using Scala/Java/Go based libraries a big plus Very proficient is SQL and other relational databases along with PySpark or Spark SQL. Proficient is using NoSQL databases. Experience in using GraphDBs like Neo4j a plus. Candidate should be able to handle unstructured data with ease. Candidate should have experience in working with MLEs and be proficient (with experience) in using MLOps tools. Should be able to consume the capabilities of said tools with deep understanding of deployment lifecycle. Experience in CI/CD deployment is a big plus. Knowledge of key concepts in distributed systems like replication, serialization, concurrency control etc. a big plus Good understanding of programming best practices and building code artifacts for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git Ability to create frameworks that can perform model RCAs using analytical and interpretability tools. Should be able to peer review model documentations/code bases and find opportunities Experience in end-to-end delivery of AI driven Solutions (Deep learning , traditional data science projects) Strong communication, partnership and teamwork skills ? Should be able to guide and mentor teams while leading them by example. Should be an integral part of creating a team culture focused on driving collaboration, technical expertise and partnerships with other teams ? Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision A self-starter who is looking to build grounds up and contribute to the making of a potential big name in the space ? Experience in Banking and financial services is a plus. However, sound logical reasoning and first principles problem solving are even more critical job role: 1. As a key partner at the table, attend key meetings with the business team to bring in the data perspective to the discussions 2. Perform comprehensive data explorations around to generate inquisitive insights and scope out the problem 3. Develop simplistic to advanced solutions to address the problem at hand. We believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development 4. Build re-usable code analytical frameworks to address commonly occurring business questions 5. Perform 360-degree customer profiling and opportunity analyses to guide new product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty 6. Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges 7. The role will be an approximate 60% IC 40% leading and the ratios can vary basis need and fit 8. Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer

Job Title: Junior AI Engineer / Data Engineer Location: Chennai Reports To : Senior AI Engineer / Data Architect Job Summary: This role is ideal for an early-career engineer eager to develop robust data pipelines and support the development of AI/ML models. The Junior AI Engineer will primarily focus on data preparation, transformation, and infrastructure to support scalable AI systems. Key Responsibilities: Build and maintain ETL pipelines for AI applications. Assist in data wrangling, cleaning, and feature engineering. Support data scientists and AI engineers with curated, high-quality datasets. Contribute to data governance and documentation. Collaborate on proof-of-concepts and prototypes of AI solutions. Required Qualifications: Bachelors degree in computer science, Engineering, or a related field. 2+ years of experience in data engineering. Proficient in Python, SQL; exposure to Azure platform is a plus. Basic understanding of AL/ML concepts.

Global Gen AI Developer Enabling a software-defined, electrified future. Visteon is a technology company that develops and builds innovative digital cockpit and electrification products at the leading-edge of the mobility revolution. Founded in 2000, Visteon brings decades of automotive intelligence combined with Silicon Valley speed to apply global insights that help transform the software-defined vehicle of the future for many of the worlds largest OEMs. The company employs 10,000 employees in 18 countries around the globe. To know more about us click here. Mission of the Role: Facilitate Enterprise machine learning and artificial intelligence solutions using the latest technologies Visteon is adopting globally. Key Objectives of this Role: The primary goal of the Global ML/AI Developer is to leverage advanced machine learning and artificial intelligence techniques to develop innovative solutions that drive Visteons strategic initiatives. By collaborating with cross-functional teams and stakeholders, this role identifies opportunities for AI-driven improvements, designs and implements scalable ML models, and integrates these models into existing systems to enhance operational efficiency. Following development best practices, fostering a culture of continuous learning, and staying abreast of AI advancements, the Global ML/AI Developer ensures that all AI solutions align with organizational goals, support data-driven decision-making, and continuously improve Visteons technological capabilities. Qualification, Experience and Skills: 6-8 Yrs Technical Skills: Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, R, SQL), and data processing tools (e.g., Apache Spark, Hadoop). Proficiency in developing, training, and deploying ML models, including supervised and unsupervised learning, deep learning, and reinforcement learning. Strong understanding of data engineering concepts, including data preprocessing, feature engineering, and data pipeline development. Experience with cloud platforms (preferably Microsoft Azure) for deploying and scaling ML solutions. Business Acumen : Strong business analysis and ability to translate complex technical concepts into actionable business insights and recommendations. Key Behaviors: Innovation: Continuously seeks out new ideas, technologies, and methodologies to improve AI/ML solutions and drive the organization forward. Attention to Detail: Pays close attention to all aspects of the work, ensuring accuracy and thoroughness in data analysis, model development, and documentation. Effective Communication: Clearly and effectively communicates complex technical concepts to non-technical stakeholders, ensuring understanding and alignment across the organization.

We are looking for "Data Scientist" with Minimum 4 years experience Contact- Yashra (95001 81847) Required Candidate profile Data Science, Agentic AI, LLM & RAC advanced machine learning (ML) and Agentic AI frameworks. generative AI, reinforcement learning, and multi-agent systems.

The Data Scientist-3 in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk, Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are deployed for real time or near real time consumption and integrated into our proprietary Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the growth trajectory of a super fast evolving digital product. Key Requirements of The Role - Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 7 - 10 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product and business teams Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets. Strong experience in NLP, time series forecasting and recommendation engines preferred Create great data stories with expertise in robust EDA and statistical inference. Should have at least a foundational understanding in Experimentation design Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch, Caffe preferred Experience with analytical programming languages, tools and libraries (Python a must) as well as Shell scripting. Should be proficient in developing production ready code as per best practices. Experience in using Scala/Java/Go based libraries a big plus Very proficient is SQL and other relational databases along with PySpark or Spark SQL. Proficient is using NoSQL databases. Experience in using GraphDBs like Neo4j a plus. Candidate should be able to handle unstructured data with ease. Candidate should have experience in working with MLEs and be proficient (with experience) in using MLOps tools. Should be able to consume the capabilities of said tools with deep understanding of deployment lifecycle. Experience in CI/CD deployment is a big plus. Knowledge of key concepts in distributed systems like replication, serialization, concurrency control etc. a big plus Good understanding of programming best practices and building code artifacts for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git Ability to create frameworks that can perform model RCAs using analytical and interpretability tools. Should be able to peer review model documentations/code bases and find opportunities Experience in end-to-end delivery of AI driven Solutions (Deep learning , traditional data science projects) Strong communication, partnership and teamwork skills Should be able to guide and mentor teams while leading them by example. Should be an integral part of creating a team culture focused on driving collaboration, technical expertise and partnerships with other teams Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision A self-starter who is looking to build grounds up and contribute to the making of a potential big name in the space Experience in Banking and financial services is a plus. However, sound logical reasoning and first principles problem solving are even more critical A typical day in the life of the job role: 1. As a key partner at the table, attend key meetings with the business team to bring in the data perspective to the discussions 2. Perform comprehensive data explorations around to generate inquisitive insights and scope out the problem 3. Develop simplistic to advanced solutions to address the problem at hand. We believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development 4. Build re-usable code analytical frameworks to address commonly occurring business questions 5. Perform 360-degree customer profiling and opportunity analyses to guide new product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty 6. Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges 7. The role will be an approximate 60% IC 40% leading and the ratios can vary basis need and fit 8. Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer .

We are looking for "Data Scientist – Agentic AI" with Minimum 15 years experience Contact- Yashra (95001 81847) Required Candidate profile advanced machine learning (ML) and Agentic AI frameworks. generative AI, reinforcement learning, and multi-agent systems. scalable AI/ML solutions.

Professor / Associate Professor Computer Science & Engineering at Rama University, Kanpur : Job Title : Associate Professor / Professor Department : Computer Science & Engineering Location : Rama University, Kanpur, Uttar Pradesh Reporting To : Head of Department / Dean, Faculty of Engineering & Technology Employment Type : Full-Time Position Summary : Rama University is seeking highly motivated and academically strong candidates for the position of Associate Professor / Professor in the Department of Computer Science & Engineering. The incumbent will be responsible for teaching, research, curriculum development, academic administration, and mentoring students while promoting a culture of innovation and excellence. Key Responsibilities : Teaching & Academic Responsibilities : Deliver undergraduate and postgraduate courses in Computer Science & Engineering. Develop and update curriculum as per industry trends and AICTE/UGC norms. Guide B.Tech, M.Tech, and Ph.D. students in academic and research projects. Conduct interactive lectures, labs, and tutorials using modern teaching tools. Research & Publications : Conduct original research in core and emerging areas such as AI, ML, Data Science, Cybersecurity, IoT, Blockchain, etc. Publish papers in reputed peer-reviewed journals and present at national/international conferences. Apply for research grants from government and industry funding agencies. Administration & Departmental Activities : Participate in departmental and university-level administrative activities. Mentor junior faculty members and students. Organize FDPs, seminars, conferences, and workshops. Collaborate with industry for academic-industry partnerships, internships, and placements. Qualification & Experience : For Associate Professor : Ph.D. in Computer Science / Computer Engineering or a closely related field. Minimum 8 years of teaching/research/industry experience, of which at least 3 years should be at the level of Assistant Professor or equivalent. At least 10 publications in Scopus/Web of Science indexed journals. For Professor : Ph.D. in Computer Science / Computer Engineering or a related field. Minimum 10 years of teaching/research experience, with at least 4 years as Associate Professor. Proven record of guiding doctoral candidates, published books/book chapters, and funded research projects. Preferred Skills & Expertise : Strong academic foundation and communication skills. Hands-on experience with programming languages (C/C++, Python, Java, etc.) and tools. Exposure to outcome-based education (OBE) and NAAC/NBA accreditation processes. Leadership qualities with ability to drive academic excellence and innovation.

5+ years of DS and AI/ML project implementation experience in one of the cloud environments (AWS/Azure/GCP). Advanced / intermediate level certification is a plus Hands-on experience in data handling using SQL and advanced analytics tools such as Python Hands on Experience in analyzing and visualizing data using tools such as Tableau, PowerBI Experience in scoping, development, validation & deployment of explanatory, predictive, and prescriptive analytic solutions Experience in stakeholder management, driving project governance, and linking analytics to business value delivered Knowledge of Deep Learning models and its applications in Natural Language Processing (NLP), AI/GenAI and Computer Vision(CV) in solving business problems Excellent presentation and communication skills Responsibilities: Participate in client workshops to identify high impact problems that could be solved through AI / ML based solutions Translate business problems (sometimes ambiguous) into clear analytic problem statements. Design a plan to develop and deploy advanced analytics solutions in collaboration with SMEs in Data Science & Engineering. Own & drive execution of the plan by demonstrating techno-functional consulting & stakeholder management capabilities. Measure and articulate how analytic results improve clients business & financial metrics. Perform a role that involves a combination of hands-on contribution, customer engagement and team management. Contribute to organization building through training, mentoring, and developing repeatable analytic approaches

Role: Solution Lead Do: - Understanding of business processes to determine problem statements in the F&A & HRO Vertical. Closely work with functional and domain experts and translate how technology can solve a business problem - Should be able to think through existing technology solutions and also have enough industry/market know how to bring in technologies from partners and develop alliances - Develop solution artefacts, value propositions with a representation of end to end business processes and mapping them back to technology solutions - Develop relationships with multiple stake holders (Below list is not exhaustive) - Functional team to understand the business needs - Technology teams to convert them into technology solutions - Sales and Pre Sales team acting as the engine enabling sales - He/she works as an individual contributor with excellent communication skills (both written and verbal) and is able to respond to RFI/RFP (RFx) and defend /present solutions with Client while working closely with the onsite Sales teams Reinvent your world.We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.