Top Data Science Jobs in India

Lead technical design, develop secure high-quality production code, drive AI-assisted engineering practices, automate remediation, evaluate vendor architectures, lead communities of practice, and coach teams on observability and responsible AI use.

Supports the PXT CFO through forecasting, budgeting, management reporting, P&L and metric analysis, financial commentary, month-close deliverables, and capitalization and amortization activities. Produces budget and review materials, responds to senior-management requests, and contributes to reporting strategy, dashboards, automation, and financial analytics for leadership and public disclosures.

Manage full-cycle recruiting for analytics, data science, data engineering, AI and machine learning, applied research, model risk, validation, and data product roles. Partner with hiring managers on role calibration, sourcing strategies, candidate evaluation, stakeholder advising, inclusive slate building, market insights, and offer negotiation. Lead multiple searches and recruiting projects while delivering strong candidate engagement and workforce planning support.

Lead and own the Data Science and AI function, driving analytics strategy, stakeholder engagement, portfolio outcomes, team leadership, technical design, and compliance with data policies to deliver measurable business value.

Own a Business Onboarding Verification workstream end-to-end: define problems, set roadmap, translate ambiguous KYB issues into measurable product requirements, partner cross-functionally, launch with guardrails, and iterate to reduce manual review, operational cost, and customer friction while improving controls and auditability.

Leads advanced data science initiatives by analyzing large structured and unstructured datasets, developing statistical and machine learning models, and generating actionable business insights. Collaborates with stakeholders, communicates recommendations to nontechnical audiences, resolves complex analytical issues, mentors junior staff, and supports strategic decision-making across business domains.

Leads a global data science organization delivering AI and machine learning solutions for workforce decision-making. Sets technical strategy, directs research from hypothesis through production, develops model and evaluation factories, advances responsible agentic engineering, and partners with technology teams on scalable enterprise data platforms. Aligns resources to measurable business outcomes, communicates with executives, fosters reuse and partnerships, and ensures compliance with organizational controls.

Leads client-facing pre-sales engagements for credit analytics solutions. Responsibilities include conducting client meetings and workshops, creating presentations and proposals, translating analytical outputs into business value narratives, demonstrating ROI, supporting strategic sales opportunities, addressing objections, and coordinating post-sale communication with Product, Data Science, and Operations teams.

Develop production-ready AI and machine learning applications using cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. The role involves deploying models, solving complex technical problems, collaborating across teams, making team decisions, sharing knowledge, and monitoring project alignment with strategic goals.

Develops advanced analytics, statistical, machine learning, generative AI, and agentic AI solutions for workforce and business challenges. Responsibilities include data mining, exploratory analysis, data preparation, predictive and prescriptive modeling, model validation and deployment, automated reporting, insight generation, data quality, responsible AI, and governance. The role uses Python, SQL, cloud platforms, and large structured or unstructured datasets to support data-driven business decisions.

Provides technical presales support for Data Engineering, Analytics, Data Science, Data Consulting, and AI services. Partners with sales and technical teams to develop proposals, presentations, and demonstrations; engages clients to understand requirements and recommend solutions; researches industries and competitors; answers technical questions; and supports cross-selling, upselling, and improved sales conversion.

Support Private Bank operating model and process excellence initiatives by analyzing data, identifying automation and AI opportunities, developing business cases, and delivering workflow, reporting, and decision-support solutions. The role coordinates business, operations, technology, and COO stakeholders; manages requirements, governance, testing, implementation, adoption, and continuous improvement while using analytics to reduce risk, improve productivity, and enhance client outcomes.

Lead product strategy and incubation for Core Intelligence, turning operational signals into AI-driven recommendations and optimization. Drive discovery, experimentation, prototypes and measurable outcomes; influence cross-functional leaders and scale reusable intelligence capabilities across Store systems.

Lead product strategy and roadmaps for data science, ML, and cloud products in healthcare. Translate business needs into technical requirements and user stories, drive Agile delivery, analyze user and market data to set metrics, design and deploy AI-powered solutions responsibly, mentor junior PMs, and ensure compliance with healthcare regulations throughout the product lifecycle.

Drives innovation across designated business streams by identifying strategic opportunities, shaping emerging technology initiatives, and supporting client-facing solution development. Collaborates with senior stakeholders and cross-functional teams to move innovation projects from ideation through implementation and adoption. Builds internal and external partnerships, facilitates workshops and research, supports business change, and contributes to innovation roadmaps, reporting, and strategic planning.

Hiring for multiple software engineering opportunities in Hyderabad, including fresher and experienced positions across Java, testing, Python, DevOps, AWS, full-stack development, data science, AI/ML, cybersecurity, Node.js, and React.js.

The role leads a team to provide healthcare-focused insights through analytics and data science, requiring strong people management, technical oversight, and a healthcare domain understanding.

Lead and mentor a data science team, develop ML solutions, drive AI/ML initiatives, ensure model performance and fairness, and foster innovation.

Entry-level R&D trainee, apprentice, or VIE supporting the Electronic Development organization and AI4EE initiative at Valeo. The role is full-time and intended for candidates pursuing or holding a BE, BTech, or MTech in AI or Data Science. Responsibilities are not detailed beyond participation in automotive mobility research and development.

The Data Science Manager will lead AI/ML solution development for clients in Supply Chain & Manufacturing, mentor data scientists, and drive business development efforts.

Lead and execute Codingal's curriculum roadmap across Coding, Math, and ELA. Manage a curriculum team and external SMEs, ensure lesson and assessment quality, strengthen teacher training and evaluation, integrate AI into learning experiences, and collaborate with product, engineering, and business teams to improve student engagement and retention. Build scalable curriculum systems, feedback loops, and launch processes to drive measurable learning outcomes and operational consistency.

Leads training deployment and delivery for Data Science, Machine Learning, AI, Generative AI, AI agent development, data engineering, big data analytics, and Power BI. Responsibilities include trainer scheduling, deployment, train-the-trainer sessions, content and lab reviews, quality tracking, student performance monitoring, college coordination, operational visits, stakeholder meetings, capacity planning, reporting, and continuous improvement.

Develop and deploy production AI/ML solutions for conduct risk and compliance, including anomaly detection, graph analytics, weak supervision, feature engineering, model evaluation, explainability, monitoring, and MLOps. Support model risk management documentation, validation, and governance in a regulated financial-services environment. Collaborate with investigations, operations, risk, and technology stakeholders, apply GenAI where appropriate, and mentor junior team members.

Lead enterprise production GenAI and machine learning initiatives for financial crime, risk, and compliance. Own the full model lifecycle, including data controls, feature engineering, validation, explainability, monitoring, retraining, and model risk governance. Build MLOps infrastructure and partner with compliance, investigations, operations, technology, audit, and senior leadership to develop defensible detection and decisioning solutions. Mentor junior data scientists and drive applied research in anomaly detection, graph analytics, weak supervision, and related methods.

Lead data science projects developing and deploying LLM and GenAI solutions for compliance and risk management. Conduct AI research, optimize model training and evaluation frameworks, analyze model effectiveness, collaborate with technology, compliance, and business teams, and communicate technical outcomes to senior stakeholders. The role requires strong Python and deep learning expertise, advanced knowledge of LLM architectures and NLP, and experience applying AI in regulatory or financial risk domains.