Principal Data Scientist

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  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. 

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  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. 

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  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. 

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  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. 

• 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  
   

• Experience working within the Databricks data science and analytics platform, including developing, training, and operationalizing models using Databricks notebooks, workflows, and integrated ML capabilities. 

• Prior experience applying data science or machine learning in an HR or workforce‑related domain, with an understanding of HR data structures, constraints, and decision contexts (e.g., employee data, organizational structures, lifecycle events). 

• Advanced degree (Master’s or PhD) in a quantitative field or equivalent depth of experience solving complex modeling problems in real‑world, production settings. 

• Experience building intelligence that supports automated or semi‑automated decisioning, recommendations, or optimization in large, distributed organizations. 

• Familiarity with deploying models alongside APIs, data products, or platforms where humans and machines interact with the same underlying intelligence. 
   

This position is located in Bangalore, India full-time and may require up to 10% travel, both domestic and international. 

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.