Intern - Data Science

In addition to our core athlete management system, Apollo is developing a new generation of AI-driven products designed to help coaches, practitioners, and athletes interact with performance content through natural language. These systems combine large language models, semantic search, and structured performance data to deliver exercises, training content, and insights directly to users through mobile and web interfaces.

Apollo is seeking a highly motivated AI & Software Engineering Intern to support the development of our emerging AI-powered data query systems. These systems allow users to interact with large sports performance datasets through natural language and voice interfaces, enabling practitioners to ask questions like: "Who had the highest countermovement jump height last season?" "What was the team’s average eccentric peak power by body mass last year?" and receive structured answers generated directly from underlying databases.

The internship will focus on improving the underlying LLM-powered data query infrastructure, including natural language query interpretation, schema understanding, SQL generation, and response validation systems. This role blends elements of AI engineering, retrieval-augmented generation (RAG), backend systems, and data infrastructure. Interns will work directly with Apollo’s engineering and product teams to improve how LLM-powered systems translate user queries into database queries and deliver reliable analytical responses.

This position is ideal for students interested in LLM systems, data infrastructure, and building production AI tools that interface directly with real-world databases.

Responsibilities

  • Build interactive dashboards and data visualizations in Tableau for internal leadership and external clients
  • Write, optimize, and maintain SQL queries to clean, transform, and analyze large datasets within Apollo’s data warehouse
  • Support data engineering workflows, including data validation, quality checks, and monitoring across Apollo’s integrated performance data sources (GPS, force plate data, medical systems, scheduling platforms, etc.)
  • Conduct exploratory and statistical analysis across athlete performance, load management, medical, and operational datasets
  • Assist in building internal analytics tools and decision-support dashboards used by leadership and client organizations
  • Support development and maintenance of machine learning model training and serving infrastructure
  • Participate in model evaluation, monitoring, and versioning workflows supporting Apollo’s AI roadmap
  • Collaborate with engineering and product teams to improve data pipelines, backend systems, and compute efficiency for AI-driven products

Requirements

  • Currently pursuing or recently completed a master’s degree in data science, Statistics, Finance, Sports Analytics, or a related field.
  • Strong proficiency in SQL and relational databases
  • Experience with data analysis, statistics, or applied sports performance datasets
  • Proficiency with analytics tools such as Tableau, Python, R, Power BI, or similar BI platforms
  • Interest in machine learning, AI infrastructure, MLOps, or data engineering
  • Strong analytical thinking, attention to detail, and ability to work with complex datasets
  • Experience with APIs (REST/JSON), Git/GitHub, Docker, or model deployment tools is a plus
  • Ability to clearly communicate insights to both technical and non-technical stakeholders
  • Ability to work independently and collaboratively in a fast-paced environment
  • Able to work 40 hours per week, in-office

    This internship offers hands-on experience working with real-world datasets used by elite professional and collegiate sports organizations. Interns will gain exposure to modern data and AI infrastructure, including machine learning workflows, model deployment, MLOps practices, and backend systems that support large-scale analytics platforms.

    Please submit your resume and a cover letter to info@apollov2.com.

    ApolloV2 is an equal opportunity employer with a commitment to hiring people with diverse backgrounds. We do not discriminate based on age, civil or family status, disability, ethnicity, gender, race, religion, or sexual orientation.