Data Science Intern (Summer 2026)

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Data Science Intern Global Finance Data Science

Johnson & Johnson

Position Summary

Join Johnson & Johnsons 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.

Key Responsibilities:

1 Predictive Analytics & Decision Support (50%)

- 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.

2. AI-Driven Process Improvement & Automation (20%)

- 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.

3. Reporting & Interactive Analytics (20%)

- 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.

4. Governance & Operational Excellence (5%)

- Support documentation model/run governance and operational performance tracking for deployed solutions.

5. Team & Development (5%)

- Provide concise status updates participate in team ceremonies and actively learn the teams standards and tooling.

Minimum Qualifications:

• 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.
• An equivalent cumulative GPA of 3.0 or higher
• Authorization to work in the United States on a permanent full-time basis is required

Preferred Qualifications:

• 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.

The anticipated base pay for this position is between $25.50/hour and $33/hour but will be based on candidates program year discipline degree and/or experience.

This position is overtime eligible.

Co-Ops/Interns may be eligible to participate in Company employee benefit programs such as medical insurance sick time and holiday pay in accordance with the terms of the applicable plans.

For additional general information on Company benefits please go to: - for severance.

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