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.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Bangalore, Karnataka, India, Gurgaon, Haryana, India

Job Description:

Position Summary

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 Data Scientist on the Global Finance Data Science team, you will develop and maintain data science solutions and supporting data pipelines for J&J’s Global Finance organization. Working with a global team of Data Scientists, Data Engineers, Finance Analysts, and ML Engineers, you will help advance the Global Finance data science and AI roadmap, deliver actionable insights to finance and business leaders, reduce manual effort through automation, and enhance the user experience.

You will operate and enhance Global Finance data science projects in production on a monthly basis, with a focus on Predictive Financial Intelligence and forecasting. You will build automated data pipelines using finance source systems, including SAP ERP and SAP S/4HANA, and platforms such as Databricks. You will also help transition proofs of concept into reliable production solutions, incorporate stakeholder feedback, develop performance tracking Power BI dashboards, and integrate conversational analytics into dashboards and applications.

Major Duties & Responsibilities

• Develop and automate data processing and modeling pipelines for large datasets from finance and ERP systems, including SAP HANA and SAP BW.
• Write scalable, production-grade Python code.
• Run and maintain data science projects in production on a monthly basis, incorporating enhancements based on evolving business needs and stakeholder feedback.
• Develop data science solutions by translating business problems into analytical approaches, processing data, identifying trends and patterns, generating insights, and communicating findings.
• Implement machine learning and statistical models for predictive analytics, time series forecasting, decision support, Generative AI, and natural language processing use cases.
• Develop Power BI dashboards and production-grade data models that translate analytical outputs into actionable business insights.
• Deploy analytical models into production and ensure adherence to requirements and standards, including version control and documentation.
• Help migrate existing Predictive Financial Intelligence projects to the Databricks production environment.
• Partner with Data Scientists, Data Engineers, Finance Analysts, ML Engineers, and stakeholders across Global Finance.
• Present results and explain complex analyses and data pipelines clearly to senior stakeholders.
• Understand and apply finance master data, Common Information Model (CIM) elements, attributes, mappings, and organizational, geographic, product, and reporting hierarchies in analytical solutions.
• Work effectively across time zones in an agile environment, balancing priorities and deadlines while fostering collaboration, innovation, and inclusion.
• Develop a strong understanding of J&J’s business, finance terminology, processes, and data landscape.

Technical Requirements

• Strong experience writing production-grade Python code and applying software engineering best practices, including modular programming, version control, and documentation.
• Hands-on experience with Databricks and cloud platforms such as AWS or Azure.
• Experience using SQL and PySpark to acquire, transform, and analyze data, with knowledge of data warehouses and ERP systems such as SAP S/4HANA.
• Interest to develop understanding of finance master data and the Common Information Model (CIM), including key data elements, attributes, mappings, and hierarchies used across financial reporting and analytics.
• Experience developing production-grade data pipelines and data models and taking analytical models from proof of concept to production deployment.
• Experience with machine learning and statistical techniques, including regression, time series forecasting, clustering, decision trees, and statistical testing.
• Experience with Power BI for data modeling, visualization, and dashboard development.
• Experience integrating conversational AI or LLM-based capabilities into dashboards and applications is preferred.
• Familiarity with Generative AI platforms and governance tools such as AWS Bedrock, Databricks Genie, Unity Catalog, OpenAI, or Claude is preferred.
• Knowledge of model deployment, API integration, and workflow orchestration tools such as Airflow or Kubernetes is preferred.
• Strong critical thinking, problem-solving, prioritization, and continuous improvement skills.
• Ability to collaborate effectively within a global team and adapt to changing priorities, deadlines, risk, and compliance requirements.

Basic Qualifications

Required Minimum Education and Experience: At least four years of relevant experience in data science, data engineering, or a related field.

Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Business Analytics, Finance, Industrial Engineering, Statistics, Mathematics, or another quantitative or STEM discipline. A Master’s degree or PhD in a relevant field is preferred.

Preferred: Experience delivering data science or data engineering solutions in a finance or commercial environment.

 

 

Required Skills:

 

 

Preferred Skills:

Advanced Analytics, Analytical Reasoning, Business Intelligence (BI), Business Writing, Collaboration, Communication, Data Analysis, Data Compilation, Data Privacy Standards, Data Savvy, Data Science, Data Visualization, Econometric Models, Execution Focus, Mathematical Software, Statistics, Technologically Savvy