Data Scientist

Dime Line Trading • Chicago, IL

34d

About The Position

Dime Line Trading is hiring a Data Scientist to help build and scale our data foundation from the ground up. This is a newly created role that will play a critical part in shaping how the firm organizes, analyzes, and leverages data to support trading and research.
You will work closely with trading, research, and engineering stakeholders to organize existing data, improve its reliability and usability, and develop predictive models that directly inform decision-making.
This role is ideal for someone who enjoys working across the full data lifecycle — from raw, unstructured data to structured analysis, insights, and models that meaningfully impact trading performance.

Requirements

• Strong proficiency in Python and/or R, including common data and modeling libraries (e.g., pandas, NumPy, scikit-learn)
• Experience with SQL for querying, transforming, and managing structured data
• Experience working with large, complex, or messy datasets
• Solid understanding of statistics, modeling techniques, and data validation
• Ability to work independently while also collaborating closely with senior members of the team
• Comfort bringing structure to ambiguous problems and evolving projects
• Clear communication skills and ability to collaborate across technical and non-technical teams

Nice To Haves

• Experience with sports analytics and/or sports betting is a plus

Responsibilities

• Audit, organize, and document existing data sources across the firm
• Clean, structure, and transform data to make it accessible, reliable, and scalable
• Design and maintain data pipelines and workflows that support ongoing research and trading initiatives
• Build, test, and iterate on predictive models using historical and real-time data
• Partner with internal teams to understand trading and development initiatives and translate them into data-driven solutions
• Create clear analyses, visualizations, and summaries to communicate findings and model results to both technical and non-technical stakeholders
• Help establish best practices around data quality, versioning, documentation, and reproducibility

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed