Data Scientist at Dime Line Trading

Chicago, Illinois, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Jun, 26

Salary

0.0

Posted On

09 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, R, SQL, Pandas, NumPy, Scikit-learn, Data Transformation, Data Pipelines, Predictive Modeling, Statistics, Data Validation, Communication, Data Quality, Versioning, Documentation, Reproducibility

Industry

Financial Services

Description

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. What You’ll Do 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 We’re Looking For 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 Experience with sports analytics and/or sports betting is a plus

Responsibilities

The Data Scientist will be responsible for auditing, organizing, and documenting existing data sources, as well as cleaning, structuring, and transforming data to ensure reliability and scalability. This role involves designing data pipelines and building, testing, and iterating on predictive models that directly inform trading decision-making.