Data Science Intern (Summer 2026)

Johnson & Johnson Innovative Medicine•New Brunswick, NJ

2d•$26 - $33•Onsite

About The Position

Join Johnson & Johnson’s Global Finance Data Science team to build production-minded analytics and AI solutions at enterprise scale. You will work with a global team of Data Scientists, Data Engineers, Finance Analysts, and ML Engineers to advance the data science and AI roadmap for Global Finance: delivering predictive insights, automation that reduces manual workload, and interactive decision-support experiences. You will contribute across the solution lifecycle: problem framing, proof-of-concept, development, deployment, and adoption. Ensuring the right level of automation, integration, and governance for real-world use.

Requirements

Pursuing a BS/MS in a quantitative discipline (e.g., CS, DS, Statistics, Engineering, Economics/Finance, Operations Research).
Strong Python proficiency with evidence of clean, structured code (projects, research, internships, or competitions).
Strong SQL skills and comfort working with large datasets (joins, aggregations, window functions preferred).
Solid foundations in statistics and machine learning; ability to explain modeling choices, assumptions, and trade-offs.
Strong communication skills: can present complex analysis clearly to technical and non-technical stakeholders.
Candidates must be pursuing an undergraduate or Fifth Year Master’s degree in Data/Computer Science, Engineering, Data Analytics, or like majors with an expected graduation date between December 2026 - May 2028.
An equivalent cumulative GPA of 3.0 or higher
Authorization to work in the United States on a permanent, full-time basis is required
Ability to temporarily relocate to a different state within the United States for rotational assignment is required

Nice To Haves

Experience taking a model from notebook → reproducible pipeline (packaging, tests, CI/CD concepts, or workflow tooling).
Exposure to cloud/data science platforms (e.g., AWS, Domino) and scalable compute patterns.
Experience with one or more: time-series forecasting, NLP, or experimentation/causal inference.
Built interactive analytics products end-to-end (Power BI/Tableau dashboards and/or Dash/Streamlit apps).
Familiarity with workflow automation tooling (e.g., Alteryx) and/or orchestration concepts.
Demonstrated ability to operate in ambiguity, drive clarity with stakeholders, and deliver measurable impact.
Leadership experience is preferred.
Some knowledge of 1 programming language (Python, R), Tableau/PowerBI, cloud platforms like AWS or Azure, and MS Excel is preferred.

Responsibilities

Develop and evaluate statistical/ML models for financial forecasting and decision support (e.g., time series, supervised learning).
Engineer features and datasets from large enterprise sources; apply rigorous validation and error analysis.
Communicate results with clear business context; translate insights into actions and measurable outcomes.
Design and prototype AI-enabled process improvements, including targeted Generative AI use cases.
Build repeatable workflows (automation/orchestration as applicable) and contribute to scalable integration patterns.
Apply engineering discipline: version control, reproducible pipelines, documentation, and basic monitoring metrics.
Develop interactive dashboards and analytics products (Power BI/Tableau) and/or lightweight apps (Dash/Streamlit).
Partner with stakeholders to define requirements, iterate quickly, and drive adoption through usability-focused design.
Support documentation, model/run governance, and operational performance tracking for deployed solutions.
Provide concise status updates, participate in team ceremonies, and actively learn the team’s standards and tooling.