# Data Scientist

**Company:** [Twenty First Group](http://jobs.workable.com/companies/wC4fdUXquiQkBwSnWSoveP.md)
**Location:** London, United Kingdom
**Workplace:** hybrid

[Apply for this job](http://jobs.workable.com/view/f6f5f663-713b-4016-b2ac-d7a6f6c5ebc3)

## Description

### Data Scientist, Sports Betting

### Role Overview

We're looking for a Data Scientist to join our Sports Betting vertical. You’ll develop predictive models, contributing to our growing portfolio of pre-match and in-play products and services for the sports betting industry.

### What You’ll Do

-   Modelling & Analysis: Develop, train, and evaluate predictive models using machine learning and statistical techniques, with a focus on probabilistic and Bayesian approaches. Contribute to the modelling lifecycle from feature engineering and training through to validation and deployment.
-   Data Work: Query, clean, and explore datasets using Python and SQL to surface patterns and support model development.
-   AI-Assisted  Development: Leverage AI tools to accelerate and improve your day-to-day workflow.
-   Quality & Rigour: Apply good model development discipline through version control, testing and documentation.

## Requirements

### What You’ll Bring

-   Passion for Sport: You follow sports and understand the context of the data and markets we build for. Comfortable with sport-driven modelling decisions.
-   Machine Learning & Statistics: Solid grounding in machine learning, supervised and unsupervised methods, and classical statistical techniques. Comfortable working with probabilistic models, uncertainty estimation and Bayesian inference.
-   Model Development: Understanding of the full model training pipeline, including data preparation, feature selection, model selection and model validation.
-   Experience: Hands-on experience building and evaluating models in a data science or quantitative context.
-   Python & SQL: Comfortable using python and SQL for data exploration, feature development and modelling workflows.
-   Communication: Able to present findings clearly to both technical and non-technical audiences.

### Nice to Haves

-   Simulation: Experience with Monte Carlo methods or probabilistic simulation.
-   AI Integration: Comfortable using AI-assisted coding tools such as Claude Code or Cursor as part of your everyday workflow, and open to integrating them deeper into how you model and build.

### What We Look For

-   Curiosity: You are naturally curious about the “Why”. You look at data and customer behaviour to inform your decisions. 
-   Collaborative & Open: You treat your work as a starting point for collaboration. You contribute to shared knowledge and code bases, and value engaging with your peers to build solutions.
-   Continuous Development: You are keen to develop knowledge and skills, keeping up to date with relevant developments and applying new learning where appropriate.

## Benefits

### What We Offer

-   Hybrid working out of our London office (Farringdon) - most of our staff come into the office about twice a week
-   Salary based on our external benchmarking framework, plus eligibility for a bonus scheme
-   Private health insurance, occupational life cover, and income protection insurance
-   Personal days, including birthdays and health and wellness days
-   AI forward culture including Claude Code Premium subscription