Data Science Intern, Centerfield

• Education: Currently pursuing a Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field
• Programming: Solid foundation in Python and familiarity with core data libraries (e.g., pandas, NumPy, scikit-learn) through coursework, research, or personal projects
• ML & Stats Fundamentals: Working understanding of machine learning concepts and applied statistics - regression, classification, evaluation metrics, and basic experimental thinking
• Data Skills: Comfortable querying and manipulating data with SQL, and curious about working with large, messy, real-world datasets
• GenAI Curiosity: Genuine interest in LLMs and Generative AI, with some hands-on exposure (prompting, an API project, a course, or experimentation) even if not yet professional
• Mindset: Self-starter who communicates clearly, asks good questions, and is eager to take a problem from notebook to a result the team can use

Desirable

• Centerfield is looking for a curious, hands-on Data Science Intern to work alongside our Data Science team on the systems that turn millions of customer conversations into intelligence
• You’ll contribute directly to our call intelligence and customer data platforms - helping us extract behavioral signals from phone calls, validate predictive models, and activate that intelligence to personalize experiences for over 150 million shoppers annually
• This is a builder’s internship: you’ll write real code, work with real data, and ship work that informs real business decisions, all with the mentorship and support of an experienced DS bench
• Trait Extraction & Analysis: Analyze call transcripts and help build and refine rules that extract behavioral and intent signals, measuring their accuracy against human-labeled benchmarks
• Model Validation: Support the team in validating predictive models and traits feeding into our customer data platform - quantifying how well signals correlate with conversion, retention, and customer value
• Data Exploration: Profile and clean high-volume data, surface patterns and quality issues, and translate findings into clear, actionable summaries for the team
• LLM & GenAI Experimentation: Get hands-on with modern GenAI workflows -prompting, evaluation, and lightweight RAG experiments - to help assess summary quality and reduce hallucinations in production outputs
• Communicate Findings: Build charts, notebooks, and short write-ups that make your analysis easy for both technical and business stakeholders to act on

• At Centerfield, we use AI tools internally to support efficiency and fairness in our hiring process, including resume screening and administrative tasks
• Candidates are welcome to use AI tools ethically to prepare for interviews, such as practicing responses or researching questions. However, all responses during the interview process should reflect your own knowledge, experience, and judgment
• The use of AI tools to generate responses during live interviews, technical assessments, or written submissions is not permitted unless explicitly stated otherwise
• Interviews will take place after resumes have been screened for the minimum requirements. Please note that this position is not restricted solely to the responsibilities listed above and that the job scope and responsibilities are subject to change