Principal Data Scientist

Johnson & Johnson Services, Inc. is recruiting for a Principal Data Scientist located in Pune, India or Bangalore, India.

Caring for the world, one person at a time has inspired and united the people of Johnson & Johnson for over 130 years. We embrace research and science—bringing innovative ideas, products and services to advance the health and well-being of people.

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.

Thriving on a diverse company culture, we celebrate the uniqueness of our employees and are committed to inclusion. Johnson & Johnson is proud to be an equal opportunity employer.

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.

You will work at the intersection of advanced analytics, applied AI, and HR domain expertise, ensuring workforce intelligence is not only accurate and scalable, but actionable, ethical, and trusted. Your work will move beyond insight delivery to directly shaping how decisions are made, automated, and continuously improved across the employee lifecycle.

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.

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
  

Preferred:

• 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.
  

Other:

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