Core Data Scientist Intern
Posted on 10/27/2025

SCOR
Compensation Overview
$22 - $24/hr
Charlotte, NC, USA
Hybrid
Hybrid role: 3 days in-office per week, 2 days remote.
The Data Science Intern will work with a team of data scientists, data engineers, and actuaries. You will learn to apply analytical and software engineering skills to solve business problems arising in mortality risk quantification, insurance pricing, explainable/interpretable machine learning, and ML fairness. Other job function expectations include: using tools such as python, jupyter, git, and communicating outcomes using MS PowerPoint.
- Pursuing Masters or Bachelor’s degree, preferably in a quantitative field (CS, Engineering, Math, Data Science, etc.)
- Python – should be able to write working python code
- Probability, statistics, and/or machine learning related coursework
- Strong academic performance and analytical thinking
- Hands-on experience with data tools and projects
- Effective communication and collaboration skills
Hybrid work policy -SCOR is committed to an “in-office” culture where people can collaborate, exchange ideas and establish stronger working relationships while still providing flexibility. To support employee work life balance and increase opportunities for employees to excel every day, SCOR operates with a hybrid working arrangement. SCOR employees work 3 days per week in an office with the flexibility to work 2 days per week remotely.
Candidates must have valid authorization to work in the U.S. without the need for employer sponsorship now or in the future.
Pay Range: $22.00 - 24.00 hourly rate. Actual salaries may vary based on various factors including but not limited to location, experience, role and performance. The range listed is just one component of SCOR's total compensation package for employees.
- Participate in an intensive 11-week data science internship and learn how data science is practiced in the industry
- Work as part of an agile team of data scientists, actuaries, and machine learning engineers
- Assist data scientists in training/interpreting ML models, and conducting experiments
- Assist data scientists in writing ML pipelines, while applying SOLID design principles to develop analytics software
- Assist data scientists in understanding financial impact of machine learning models
- Research and present a final project to Americas Data Analytics staff
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