Manager Data Science

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

As a Manager, Data Science (M1) in the Global Finance Data Science Team, you will serve as the technical and business-domain subject matter expert accountable for the end-to-end execution of data science products and AI-enabled applications across Global Finance and Compliance. The role will primarily lead vendor application-development teams, ensuring solutions are delivered efficiently, on time, and to a high standard of quality.

This role combines data science and Finance process expertise with application delivery leadership. You will translate business problems into clear requirements and executable solution designs, then guide vendor teams in developing production-ready models, applications, APIs, workflows, and integrations that connect with transactional systems, including SAP S/4. You will ensure the latest fit-for-purpose technologies are applied responsibly to improve speed, automation, controls, user experience, and decision quality.

You will work directly with Finance, Compliance, and Technology stakeholders to understand processes, pain points, controls, and user needs, and convert them into applications and solutions that solve the business problem. You will own execution from requirements and design through development, testing, deployment, adoption, and ongoing production support, coordinating vendor teams and enterprise partners throughout delivery.

Lead and manage large vendor application-development teams, establishing clear requirements, work plans, milestones, quality expectations, and accountability for business outcomes.

• →Serve as the data science and application-delivery SME, working with stakeholders to define business problems, document functional and technical requirements, clarify acceptance criteria, and shape fit-for-purpose solution designs.
• →Own end-to-end execution of data science products and applications, from stakeholder discovery, requirements definition, and solution design through vendor development, testing, validation, deployment, adoption, and production support.
• →Design and implement financial process and workflow applications that combine data, business rules, predictive models, Generative AI, approvals, evidence capture, and user-facing experiences to simplify and automate complex Finance processes.
• →Design and implement risk management applications in the Compliance space, including solutions that support business operations, compliance oversight, and audit stakeholders across the three lines of defense.
• →Architect and deliver integrations with enterprise transactional and financial systems, including SAP S/4, using governed data pipelines, APIs, events, services, and workflow orchestration.
• →Lead the development of real-time and near-real-time scoring services, transaction monitoring capabilities, alerting, case prioritization, and human-in-the-loop review workflows for financial and compliance use cases.
• →Lead the design and delivery of label-harvesting and human-in-the-loop forecasting applications, such as Gross-to-Net solutions, where data science models generate predictions and business users can review, approve, override, or refine forecasts with structured reason codes and commentary. Ensure user decisions are captured as governed feedback for auditability, model monitoring, retraining, and continuous improvement of future predictions.
• →Guide the application of machine learning, statistical methods, time series forecasting, NLP, Generative AI, and agent-enabled workflows, ensuring outputs are accurate, explainable, traceable, and suited to the business decision.
• →Establish engineering and MLOps standards for reusable code, model and prompt lifecycle management, automated testing, CI/CD, monitoring, observability, documentation, release governance, incident response, and ongoing model performance management.
• →Ensure products meet enterprise requirements for security, privacy, compliance, scalability, resilience, maintainability, data quality, access control, and audit readiness.
• →Embed controls, approval workflows, lineage, evidence capture, decision logs, explainability, and complete audit trails into product and application design.
• →Partner with product owners and senior business and technology stakeholders to define outcomes, requirements, success measures, delivery tradeoffs, adoption plans, and operating models.
• →Direct vendor execution across scope, estimates, staffing, milestones, dependencies, risks, defects, releases, documentation, knowledge transfer, and production readiness; proactively remove blockers and hold partners accountable for efficient, timely, and high-quality delivery.
• →Evaluate and apply current data science, Generative AI, cloud, integration, workflow, and application-development technologies and patterns to accelerate delivery, improve solution quality, and create reusable capabilities within enterprise standards.

• Minimum of 7 years of relevant experience in data science, machine learning, AI, analytics engineering, software engineering, or enterprise application delivery, including demonstrated ownership of complex initiatives delivered through vendor or partner teams.
• Bachelor’s degree required in Computer Science, Engineering, Data Science, Statistics, Mathematics, Business Analytics, Finance, or another quantitative discipline; Master’s degree preferred.
• Demonstrated experience leading vendor or outsourced application-development teams, with strong delivery governance, prioritization, issue resolution, quality management, and accountability for scope, schedule, and outcomes.
• Strong hands-on foundation in machine learning, statistics, Python or R, SQL, data engineering concepts, software development, and production-grade analytical application design.
• Proven experience building and operating applications that operationalize analytics, machine learning, or AI through web applications, APIs, backend services, workflow tools, or decision platforms.
• Experience designing and implementing financial process and workflow applications, including business rules, approvals, exception management, evidence capture, and role-based user experiences.
• Experience designing risk management or compliance applications in regulated environments, with explainability, traceability, governance, controls, and audit-ready reporting built into the solution.
• Experience connecting analytical products and applications to transactional and financial systems, including SAP S/4, through APIs, event-driven patterns, integration platforms, governed data pipelines, or similar enterprise integration methods.
• Experience with real-time or near-real-time model scoring, transaction monitoring, alert generation, case prioritization, streaming or event-based processing, and the operational monitoring of scoring services.
• Experience designing label-harvesting or human-in-the-loop applications that present model-generated forecasts or recommendations for user approval or adjustment, capture structured overrides and commentary, maintain decision history and audit trails, and feed validated outcomes back into model evaluation and retraining.
• Experience delivering predictive analytics, forecasting, anomaly detection, risk scoring, NLP, Generative AI, or agent-enabled solutions from proof of concept through production.
• Hands-on experience with Generative AI patterns, including structured prompting, grounding with enterprise data, tool or workflow integration, validation, guardrails, evaluation, and quality controls.
• Experience deploying and supporting solutions in AWS and/or Azure using relevant services for compute, containers, serverless processing, machine learning, API management, data integration, identity, security, monitoring, and observability.
• Strong understanding of MLOps, DevSecOps, CI/CD, automated testing, version control, model and prompt lifecycle management, documentation, release governance, incident management, and production support.
• Ability to evaluate technical tradeoffs, guide architecture and data decisions, manage delivery risk, and balance speed, control, scalability, and long-term maintainability.
• Strong communication and stakeholder management skills, including the ability to translate complex technical concepts into clear business outcomes, risks, recommendations, and execution plans for senior leaders.
• Proven ability to facilitate stakeholder workshops, understand complex Finance or Compliance processes, translate business needs into clear functional and technical requirements, and guide teams toward practical solutions.
• Experience collaborating across Finance, Compliance, Audit, Technology, Cybersecurity, Enterprise Architecture, Data Engineering, and external delivery partners in a global or matrixed enterprise.

This position is based in Pune, India and requires approximately 25% travel to work directly with stakeholders on requirements, process understanding, solution design, and delivery.

This position might require relocation to another J&J branch in India.