Principal Data Scientist

Job Title: Principal Data Scientist Company: Johnson & Johnson Job Category: Machine Learning Roles & Responsibilities: Job Description Johnson \& Johnson Services, Inc. is recruiting for a Principal Data Scientist located in Bangalore, India. With a global footprint spanning more than 250 operating companies and a workforce of over 125,000 employees, Johnson \& Johnson is uniquely positioned to lead the future of health—and the future of work. If you have the talent and ambition to shape how organizations understand, enable, and support their people at scale, Johnson \& Johnson offers the opportunity to make a lasting impact. HR Data \& Intelligence sits at the heart of Johnson \& Johnson’s HR Digital ecosystem, architecting the intelligence layer that shapes how the company understands, engages, and mobilizes its global workforce. This organization builds and operationalizes enterprise\-scale data, analytics, and AI capabilities that do more than inform decisions—they reshape how HR plans, predicts, personalizes, and performs. By unifying data science, employee listening, knowledge management, and responsible AI, HR Data \& Intelligence is transforming workforce signals into strategic advantage, ensuring HR is not only insight\-led and future\-ready, but a trusted steward of ethical, human\-centered intelligence at scale. As a Principal Data Scientist , you will design, build, and operationalize predictive and prescriptive models that power Johnson \& Johnson’s intelligent HR workflows at global scale. This role is responsible for creating model‑driven solutions intentionally designed for consumption by both humans and machines—from AI‑enabled decision engines and automation to explainable insights embedded in leader and HR experiences. Key Responsibilities * Design, build, and operationalize predictive models that generate signals, features, and recommendations consumed directly by intelligent systems and decision workflows, as well as by humans through explainable, experience‑led interfaces. * Enable end‑to‑end intelligent workflows by embedding predictive intelligence into products, platforms, and processes—ensuring models are deployed, monitored, and continuously improved in production rather than delivered as standalone analyses. * Act as a technical authority for model‑driven data products, contributing to how intelligence is created, validated, governed, and consumed across both human‑led and machine‑led decision paths. * Partner with product, engineering, and experience teams to ensure human‑facing experiences and machine‑facing interfaces (signals, features, APIs) are designed together as a single, coherent system. * Adhere to enterprise standards and practices for model explainability, fairness, privacy, and responsible AI, ensuring predictive solutions are trustworthy, auditable, and appropriate for use at global scale. * Translate ambiguous, complex business problems into scalable analytical and modeling frameworks, guiding when decisions should be automated, augmented, or explicitly human‑controlled. Work Location: Bengaluru, Karnataka, India Availability: Full time

Qualifications Required: * Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field * 5\+ years of experience designing, building, and deploying predictive or machine\-learning models in production environments, where outputs are consumed by systems, workflows, applications, and end users * Strong proficiency in modern data science and ML tooling (e.g., Python, ML frameworks, feature engineering, model evaluation), with a clear understanding of how models move from experimentation to operational use * Demonstrated ability to think in terms of signals, features, and decision logic, and to design models that integrate cleanly into automated or augmented decision workflows * Experience working on complex, scaled data environments, collaborating closely with engineering, product, and platform teams to deliver durable, production\-ready solutions * Working knowledge of model explainability, fairness, privacy, and responsible AI practices, and the discipline to apply enterprise standards consistently when building and deploying models * Strong problem\-framing skills, with the ability to translate ambiguous business or system challenges into well\-structured modeling approaches without relying on prescriptive requirements Key Skills: Machine Learning, Python, Feature Engineering Salary: Not disclosed