Data Scientist Senior
Core
Developing predictive models and trading strategies for sports trading markets.
Role type
Senior IC data scientist (sports trading)
Builds
Production models and trading strategies for sports markets
Domain
Sports betting and financial trading
Deliverable
production ML models
Required skills
probability theory, statistics, machine learning, predictive modeling, data analysis, model design, back-testing, optimization
Preferred skills
domain expertise in sports, creativity in model design
Technologies
polars, duckdb, dbt
Responsibilities
Designing predictive models for sports results predictions, Back-testing and optimizing models, Cooperating with the trading department
Seniority
Senior, hands-on IC
Rewrite
## About the role
As a Senior Data Scientist at Ematiq, you will be responsible for developing models and trading strategies deployed in sports trading markets.
To maximize the chances of developing models with a competitive edge, you will combine insights from the sports domain with your experience in predictive modeling and data analysis. We envision the ideal candidate as someone who can engage with domain experts to better understand the modeling problems at hand and leverage that information to deliver effective models.
Our expectation is that candidates will be able to design models that are deployed in production and used for trading in the markets. You will be working in a deliberately flat organization where your opinion will be heard and considered from day one.
To help you focus on modeling and developing trading strategies, you will be supported by data engineers who are part of the Quant team. They will assist you in accessing data conveniently, even when datasets reach terabytes in size. You will also receive guidance from software engineers when delivering models and trading strategies to production.
## Responsibilities
- Designing predictive models for sports results predictions
- Back-testing and optimizing models
- Cooperating with our trading department
- Working with a modern Data Science stack using libraries like polars, duckdb, dbt
## Requirements
- Strong background in mathematics, preferably in probability theory, statistics, or machine learning
- Proficiency in developing data-drive models
- Creativity in designing models
Sourced via wellfound · Listed on CareerPlan, which tracks 70,000+ jobs from 20+ sources.