Lead Data Scientist- HCC

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.

We are currently recruiting for a Lead Data Scientist for our Healthcare Compliance group. This is a hybrid role based in Titusville, NJ, New Brunswick, NJ, Sao Paulo, Brazil and Bogota, Colombia.

The lead data scientist is responsible for designing, developing, and scaling data-driven, AI/ML enabled, solutions that enhance Healthcare Compliance operations globally. The role bridges compliance, analytics, technology, and business teams to identify opportunities, develop innovative solutions, and operationalize digital capabilities that improve monitoring, insights generation, risk management, productivity, and decision-making.

This role serves as a technical lead for advanced analytics, automation, generative AI, Copilot agents, and enterprise AI solutions supporting HCC functions across multiple regions and markets.

• →Design, develop, validate, and deploy machine learning models to identify potential healthcare compliance risks, anomalies, and emerging patterns.
• →Apply supervised and unsupervised machine learning techniques, including classification, clustering and anomaly detection to business questions.
• →Develop statistical and analytical methodologies to support proactive risk monitoring and risk identification.
• →Build scalable analytical pipelines and workflows using structured and unstructured data sources.
• →Evaluate model performance and continuously improve models through monitoring, retraining, and validation.
• →Query and analyze large complex datasets to create reproducible and scalable data science solutions
• →Develop and deploy Copilot Agents, chatbot solutions, and knowledge retrieval capabilities to improve efficiency and user experience in our program.
• →Ensure governance standards are incorporated in analytic work.
• →Partner with governance, compliance, and technology teams to ensure responsible AI adoption and alignment with organizational standards.

• Strong proficiency in Data Science, Machine Learning, and Advanced Analytics to develop predictive, operational, and insight-driven solutions.
• Strong proficiency in Python or R and SQL, for data extraction, feature engineering, modelling, automation, and analytics development.
• Bachelor’s degree in data science, statistics, mathematics, computer science, engineering or related quantitative field with 5 years of relevant experience; OR Masters degree with 3 years of relevant experience.
• Experience in developing and deploying ML models using common libraries and frameworks
• Experience working with NLP libraries, extracting text from documents (OCR), and generating embeddings for downstream work.
• Experience in processing and analyzing large, complex data sets for advanced analytics
• Experience in leading analytical projects and influencing cross-functional teams.
• Experience with AI, Generative AI, and Copilot technologies with the ability to translate emerging technologies into practical business solutions.

Bachelor’s degree in data science, statistics, mathematics, computer science, engineering or related quantitative field with 5 years of relevant experience; OR Masters degree with 3 years of relevant experience.

• Act as a trusted technical advisor to global compliance leaders and business stakeholders.
• Lead solution discussions, proof-of-concepts, demonstrations, and technology evaluations.
• Translate business requirements into technical solutions and drive execution from concept through deployment.
• Mentor team members and promote adoption of modern analytics and AI practices.