Internship Data Science

Af - Group - Lansing, MI

Full-time - Intern

Lansing, MI

Religious, Grantmaking, Civic, Professional, and Similar Organizations

About the position

The data science team at AF Group is looking for an intern to gain hands-on experience in applying statistics, machine learning, and natural language processing to address complex business challenges. The intern will work closely with claims and pricing business partners to deliver valuable insights and will participate in various data science tasks throughout the internship.

Responsibilities

• Perform exploratory data analysis and feature engineering.
• Build predictive models using supervised and unsupervised learning approaches on structured and unstructured data.
• Train natural language processing models to extract information from notes and scanned documents.
• Conduct hyper-parameter tuning and feature selection.
• Evaluate model performance and create exhibits such as lift charts.
• Research new machine learning and statistics algorithms/concepts/frameworks.
• Communicate results via presentations, reports, and dashboards to both technical and nontechnical stakeholders.
• Assist with peer review of code.
• Learn about risk, pricing, claims handling and gain an in-depth understanding of property and casualty insurance.
• Attend sprint planning and daily standups and present work completed during biweekly sprint reviews.

Requirements

• Have status as either senior undergraduate or graduate student (MS/MA) as of the end of the spring term.
• Hold a cumulative grade point average of 3.0 or better as of the most recent grading period.
• Be able to work full-time during normal business hours for this summer.
• Be available to begin employment between mid-May and mid-June.
• Should hold or be pursuing a bachelor's or master's degree in Data Science, Statistics, Computer Science, Mathematics, Operations Research, Engineering, Physics, Actuarial Science, or similar analytical STEM field.
• Strong knowledge of statistical modeling and machine learning algorithms, including gradient boosted trees, artificial neural networks, generalized linear models, dimensionality reduction, and clustering techniques.
• Intermediate Python programming skills, including knowledge of packages such as pandas, matplotlib, NumPy, and scikit-learn.
• Working knowledge of SQL and relational databases.
• Knowledge of natural language processing concepts, including TF-IDF, topic modeling, sentiment analysis, and word embeddings.
• Experience with Git and cloud resources like Azure or AWS.

Nice-to-haves

• Ability to present information and ideas clearly and concisely in both written and oral manner.
• Ability to establish workflows, manage multiple projects, and meet necessary deadlines while maintaining composure during stressful workloads and/or deadlines.
• Ability to maintain confidentiality.

Benefits

• Hands-on experience in a real-world data science environment.
• Opportunity to learn about risk, pricing, and claims handling in the insurance industry.