Data Science Summer Internship at MSIG USA in Warren, NJ

We are seeking a Data Science Intern to support the design, development, and evaluation of predictive models that inform business decisions across insurance / financial services use cases (e.g., risk, pricing, propensity, claims). The intern will work alongside experienced data scientists and contribute to real analyses using production-like, real-world datasets—not toy problems—while building strong foundations in applied machine learning, experimentation, and stakeholder communication.

What You’ll Do (Key Responsibilities)

Under the guidance, you will:

• Support predictive model development for use cases such as risk, pricing, propensity, and claims.
• Perform data exploration and feature engineering using Python and SQL.
• Clean and prepare datasets from multiple sources (e.g., EDP, PRS, finance/claims systems).
• Run experiments and model evaluations, including train/validation splits, performance metrics, and back-testing.
• Translate results into clear summaries and visuals for business stakeholders.
• Contribute to documentation of datasets, models, and experiments within internal repositories.

Required Skills & Competencies

• Python (Pandas, NumPy; plus scikit-learn or similar ML libraries).
• Solid understanding of statistics and probability (distributions, confidence intervals, hypothesis testing).
• Working knowledge of machine learning concepts (classification, regression, model evaluation).
• SQL: ability to query, join, and aggregate data from relational sources.
• Experience with Jupyter / VS Code and version control (Git) is a plus.

Core Competencies

• Strong analytical/problem-solving skills and curiosity about “why the data looks this way.”
• Ability to explain technical ideas in clear, simple language to non-technical audiences.
• Attention to detail and comfort working with messy, real-world data.
• Reliability, ownership, and willingness to ask questions early.

What You’ll Learn / Professional Development

During the internship, you can expect:

• Work on real business problems with measurable outcomes (e.g., underwriting, claims, finance).
• Close mentorship from experienced data scientists on coding practices, model design, and experiment setup.
• Participation in team rituals such as stand-ups, code reviews, and design discussions, learning how data science operates in an enterprise environment.
• Opportunities to present findings to business stakeholders, strengthening communication and storytelling skills. [FW: Co-Op...ob Posting | Outlook], [torchora.com]

What You’ll Gain by the End of the Internship

By the end of the internship, the Data Science Intern can expect to have:

• Hands-on experience building, evaluating, and helping deploy at least one end-to-end ML or advanced analytics use case.
• Stronger skills in Python, SQL, and statistics applied to production-like datasets.
• Exposure to industry tooling and practices (e.g., data platforms, BI tools, Git, issue tracking).
• A concrete portfolio artifact (or internal case study) to speak to in future interviews.
• Practical understanding of how data science supports insurance / financial services decisions. [Insurance...Scientist | Word], [FW: Co-Op...ob Posting | Outlook], [torchora.com]

Minimum Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Coursework or project experience in machine learning/statistics and data analysis. [velvetjobs.com], [expertia.ai]

Nice to Have

• Experience with Git-based workflows (pull requests, code reviews).
• Familiarity with model monitoring concepts or production analytics practices.
• Exposure to insurance, claims, underwriting, pricing, or financial datasets (helpful but not required).