Role OverviewJoin Quest Analytics as an intern to work on meaningful projects that contribute to real products, data solutions, and business outcomes. Interns will have the opportunity to build, analyze, problem-solve, collaborate, and make an impact.
What You Will Do
Contribute to the full software development lifecycle, build and maintain data infrastructure, and apply statistics, machine learning, and AI to explore complex healthcare data and solve real-world business problems.
Why It Might Be a Fit
We're looking for talented and motivated individuals who are already experimenting with AI, have hands-on experience using generative AI and AI-assisted development tools, and are curious about continuing to experiment with emerging technology.
Requirements
- Must live in the Kansas City metro area
- Able to work without visa sponsorship now and in the future
- Pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Data Analytics, Data Engineering, or related field
- Juniors and above preferred (2+ years of degree experience)
- Prior internship experience in data engineering, analytics, or data science is a plus
- Programming: Python and SQL
- Additional languages: C#/.NET preferred; Java or C++ also relevant
- Databases: SQL Server and relational databases; exposure to NoSQL or MongoDB is a plus
- Data & Development Tools: Databricks, Spark, Git
- Analytics & Visualization: Excel, Power BI, PowerPoint
- Frontend Development: HTML, CSS/Sass, React, and TypeScript are a plus for Software Engineering candidates
- Understanding of object-oriented programming concepts; C#/.NET experience is preferred
- Ability to troubleshoot and debug applications
- Ability to write performant SQL queries against complex data models
- Understanding of relational databases, data structures, and software development fundamentals
- Exposure to data pipelines, ETL/ELT processes, distributed data processing, APIs, or cloud-based technologies is a plus
- Familiarity with source control and collaborative development using Git
- Statistics, probability, and exploratory data analysis
- Machine learning fundamentals, including supervised and unsupervised learning
- Classification and regression techniques
- Model development, validation, and evaluation
- Feature engineering and data preprocessing
- Natural language processing (NLP)
- Python data science libraries such as pandas, NumPy, scikit-learn, or similar tools
- Data visualization and communicating analytical findings
- Experimentation, hypothesis testing, and quantitative problem solving
- Generative AI and Large Language Models (LLMs) are a plus
- Exposure to prompt engineering, embeddings, vector search, retrieval-augmented generation (RAG), or other applied AI techniques is a plus
- Strong communication and collaboration skills
- Ability to communicate data topics and results clearly
- Self-motivated, proactive, and effective in a remote environment
- Strong problem-solving mindset and team player attitude
Benefits
- Competitive salary
- Health, dental, and vision insurance
- 401(k) plan
- Paid time off
- Flexible work arrangements
- Professional development opportunities
- Collaborative and dynamic work environment
- Opportunities for growth and advancement
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