Data Scientist

• Lead architecture for one Enterprise Analytics product domain
• Mentor engineers and ensure alignment with QualCore platform standards
• Own product architecture and technical roadmap
• Lead specification reviews and architectural decisions
• Use AI-assisted engineering tools to accelerate production-quality software delivery while maintaining human accountability
• Drive platform reuse and API-first design
• Coach Product Engineers and partner with QA and Product Owners.

Product Architect – Enterprise Analytics Services

• Extract, transform, and analyze data to find insights
• Perform analytical hypothesis testing and modeling
• Provide key insight to internal and external clients
• Support sales function with data expertise and feasibility reviews
• Manage and lead cross-functional teams of analysts
• Create and maintain user interface and reporting tools

• Build and scale statistical and ML models for large audience datasets (TV, OTT, CTV), ensuring performance, reliability, and production readiness, including:
• - Statistical models (e.g., NBD, regression-based methods) for behaviour, frequency, and reach estimation
• - Deduplication and cross-platform reach estimation models
• - Forecasting models for inventory, impressions, reach, and campaign delivery
• - Predictive models for audience measurement and planning
• - Churn prediction models for retention and engagement analysis
• - Clustering models for audience segmentation and targeting optimisation
• Design and implement planning and allocation algorithms for campaign optimisation and yield management
• Translate business problems (pricing, allocation, yield optimisation) into scalable data science solutions
• Work closely with product and engineering to productionise and integrate models into decision systems
• Contribute to AI-driven feature development across planning and measurement

Senior Data Scientist – Part-Time

• Build and scale statistical and ML models for large audience datasets (TV, OTT, CTV)
• Design and implement planning and allocation algorithms for campaign optimisation and yield management
• Translate business problems (pricing, allocation, yield optimisation) into scalable data science solutions
• Work closely with product and engineering to productionise and integrate models into decision systems
• Contribute to AI-driven feature development across planning and measurement

Senior Data Scientist

• Design, build, and evaluate classical machine learning models for business-critical use cases (classification, regression, ranking, anomaly detection, time-series forecasting).
• Apply probabilistic and Bayesian modeling techniques to quantify uncertainty and inform decision-making under uncertainty; leverage tools like PyMC and PyMC-Marketing for Bayesian workflows.
• Perform rigorous EDA, feature engineering, and data wrangling on large structured and semi-structured datasets using Python and SQL.
• Collaborate with data engineers and analytics engineers to source, clean, and validate data pipelines feeding ML workflows.
• Develop, track, and communicate model performance metrics; identify degradation signals and recommend retraining or improvement strategies.
• Translate business questions into well-framed statistical problems and present findings clearly to technical and non-technical stakeholders.
• Maintain clean, reproducible, and well-documented code and notebooks following team engineering standards.

• Managing a team of data analysts and data scientists responsible for a portfolio of diagnostic, predictive, and prescriptive analytics projects
• Supports the continuous evolution and strategy of data science capabilities
• Oversees and engages in deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making
• Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps
• Communicates complex analytical findings and implications to business leaders

Manager, Data Science

• Play a pivotal role in transforming critical infrastructure processes
• Embed in a scrum team for daily design, measurement, and delivery
• Own day-to-day decisions, mentor others, and ship to production
• Design and analyze experiments for agent experiences

UX Data Scientist

• Own the complete Reporting function.
• Lead the Data & Reporting team with end-to-end ownership.
• Review technical solutions before delivery.
• Guide team members and establish coding and reporting standards.
• Prioritize work based on business impact.
• Develop a strong understanding of business workflows and data across multiple modules.
• Understand how data flows between different systems.
• Identify downstream reporting impacts whenever application changes occur.
• Work closely with Engineering Leads, QA, Product and Business teams.
• Independently interact with Client Account Managers and business stakeholders to gather reporting requirements.
• Provide timely updates, communicate risks and manage stakeholder expectations.
• Analyze incoming requests and perform effort estimation.

Lead – Data & Reporting

Senior Data Scientist – AI Specialist

• Drive the strategy and planning, execution, and completion of all data management activities and deliverables within assigned scope ensuring quality, compliance standards, consistency, and efficiency.
• Proactively evaluate and manage resource demand, allocation, utilization, and delivery to meet current and future business needs. Ensure timely and effective maintenance of functional planning systems.
• Independently and effectively manage issue escalations, adopting appropriate escalation pathways.
• Anticipation, early detection, prevention and management of risks and issues impacting departmental deliverables and activities.
• Collaborate with internal cross-functional colleagues and external partners to define the data integration strategy for assigned programs/projects.
• Collaborate with external partners on data management related deliverables including co-development programs.
• Ensure staff/team compliance with department SOPs, policies, and regulatory guidance documents.
• Lead or contribute to the development and maintenance of departmental policies, procedures, training, and standards.
• Contribute to the development of functional vendor contracts and oversee delivery in line with agreed milestones and scope of work, R&D business planning and budget estimates.
• Drive the enhancement of functional, technical and/or scientific capabilities within data management.
• Influence the external industry and/or regulatory environment through active engagement in industry forums and working groups.
• May serve as a business process or system owner for Data Management Processes or Systems.

Senior Manager, Clinical Data Acquisition

• Architect data lake/lakehouse platforms for forecasting, anomaly detection, and BI/analytics using Databricks, Spark, and Delta-style patterns.
• Set and enforce engineering standards for data modeling, integration, and pipeline design across teams/products.
• Lead cloud event-driven/microservices architecture that integrates with web front ends and APIs.
• Design, build, and optimize batch and event-driven ELT/ETL pipelines for analytical and operational workloads.
• Build ingestion/transformation flows aligned to bronze/silver/gold, with validation, CI/CD, testing, and observability baked in.
• Implement scalable time-series forecasting training and inference across categories.
• Build model monitoring (RMSE/MAE/bias/coverage/residuals) with dashboards and automated alerts.
• Develop residual/outlier detection using Z-scores, PELT change points, and confidence-interval breach checks.
• Implement classification/risk-scoring models (e.g., Logistic Regression, Random Forest, XGBoost, clustering, HMMs) for anomaly classification and category risk.
• Automate data quality and schema validation (missing dates/targets, type changes, schema evolution, allocation shifts).

Data Scientist III

• Gather data from internal stakeholders
• Prepare workpapers for filing tax returns for federal, state, and local entities.
• Maintain supporting workpapers and all correspondences in the documents repository
• Complete tasks assigned by the supervisor

Associate Data Scientist

• Developing credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
• Design and run experiments to optimise approval rates, loss rates, and profitability
• Partner with product squads to embed decision logic into real-time systems
• Ensure data quality, compliance, and ethical use of models across all decisioning processes
• Mentor product squads on best practices in experimentation and data-driven decision making
• Provide models to optimise outcomes in collections, churn management and user retention

Data Science Manager – Credit

• Support Gainwell's Medicaid and public sector analytics initiatives by leading advanced data science activities across complex healthcare and enterprise datasets.
• Apply statistical modeling, machine learning, and scalable analytics techniques to generate actionable insights.
• Function independently within a business area while collaborating across multiple teams.
• Influence analytical approaches, mentor junior staff, and contribute to improving data science practices.
• Lead data ingestion, cleansing, transformation, and aggregation efforts for large scale datasets.
• Design and implement advanced feature engineering, statistical estimation, and hypothesis testing techniques.
• Develop, validate, and refine machine learning and statistical models.
• Analyze healthcare and enterprise datasets to surface complex, high impact, actionable insights.
• Drive iterative model development and support continuous integration and deployment of analytics solutions.
• Optimize data science solutions for performance, scalability, and production readiness.
• Collaborate with business stakeholders, data engineers, architects, and analysts to align analytics outputs with business objectives.
• Provide technical leadership and guidance to junior data scientists and analysts.

• Lead and manage a team of senior associates and associates within the Banking/Investing vertical, driving team performance, productivity, and adherence to KPIs, identifying training needs and support capability building within the team
• While performing research, oversee end-to-end project execution within the Banking/Investing domain
• Ensure timely delivery of high-quality research
• Develop and share subject knowledge expertise with team members, to help them navigate complex projects and act as a Subject Matter Expert (SME) for domain-specific queries
• Support onboarding and training new team members, conduct knowledge-sharing sessions on Banking/Investing metrics
• Develop and maintain SOPs, guidelines, and knowledge of repositories
• Collaborate with analysts, to understand requirements and align on deliverables
• Provide regular updates on progress, challenges, and key insights
• Track and evaluate team performance metrics, provide regular feedback to members in areas to improve, ensure timely delivery of projects with high accuracy (target: ≥97%)
• Proactively manage escalations and resolve delivery challenges
• Drive continuous improvement initiatives within the team, identify opportunities to improve workflows, and optimize processes

Assistant Manager – Data Research

• Develop and maintain advanced Python-based applications in the Generative AI domain, ensuring high performance, reliability, and scalability.
• Implement and optimize Generative AI models, including GPT, LLAMA, Mistral, FLAN T5 and other cutting-edge AI technologies, to create innovative solutions and knowledge graph.
• Collaborate with cross-functional teams to integrate AI functionalities into broader systems and applications.

• Lead, mentor, a team of data scientists, fostering a collaborative and innovative environment.
• Provide technical guidance and oversight throughout the solution development lifecycle.
• Drive best practices in MLOps, model development, testing, and deployment.
• Stay abreast of the latest advancements in AI/ML and recommend their application to relevant business challenges.
• Design, build, and deploy end-to-end AI/ML models and systems that address critical after-sales service needs.
• Develop robust, scalable, and production-ready code for AI ML applications.
• Perform data exploration, feature engineering, model training, evaluation, and optimization.
• Collaborate closely with product managers, data scientists, business stakeholders, and IT teams to understand requirements, define project scope, and deliver impactful AI ML solutions.
• Identify opportunities to leverage AI ML to improve efficiency, reduce costs, and enhance customer satisfaction in after-sales service.
• Debug and troubleshoot complex AI ML systems and data issues.

Data Science and AI Manager

• In Data Science we work with the data from fast changing consumer goods world. Data comes both from standardized databases and from online retail channels in various forms like semi-structured text in various languages, images or precise numeric values.
• Currently we are looking for a new colleague to join the team and assist developing new and improving existing ML models according to our client feedback and suggest new ways looking at the data which would result in new product

• As a Consultant (Analytics) you will be a pivotal player in modernizing telecom financial operations.
• Bridging the gap between implementation and architectural strategy, you will design, develop, and deploy advanced AI/ML, Generative AI, and Agentic AI solutions tailored for the finance domain.
• Your work will transition complex financial workflows—such as Forecasting as a Service, Explainability framework, Funnel Forecasting, Customer Profitability etc.
• Own the end-to-end lifecycle of critical AI models while translating complex technical results into compelling business narratives for finance leadership.
• Design and deploy core AI/ML and Generative AI solutions to optimize financial operations.
• Build and orchestrate Agentic AI workflows to automate multi-step financial analysis and decision-making processes.
• Utilize foundational models and AI assistants (e.g., Claude, GitHub Copilot) to rapidly prototype, iterate, and deliver agile AI solutions to meet dynamic business needs.
• Engineer robust data pipelines and write complex SQL/BigQuery queries to extract and transform large-scale financial datasets using GCP and Python.
• Implement MLOps best practices to ensure continuous integration, deployment, and monitoring of financial AI models in production environments. Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.

Senior Consultant – Data Science

• Lead teams in assessing governance, risk, and control programs
• Mentor junior staff to develop their skills
• Utilize technology resources and data visualization tools for project success
• Identify opportunities for innovation and process enhancement

Data Scientist jobs in India

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Product Architect – Enterprise Analytics Services

Data Scientist

Senior Data Scientist – Part-Time

Senior Data Scientist

Data Scientist

Manager, Data Science

UX Data Scientist

Lead – Data & Reporting

Senior Data Scientist – AI Specialist

Senior Manager, Clinical Data Acquisition

Data Scientist III

Associate Data Scientist

Data Science Manager – Credit

Data Scientist

Assistant Manager – Data Research

Senior Data Scientist

Data Science and AI Manager

Data Scientist

Senior Consultant – Data Science

Senior Manager – AI Governance