Junior Data Scientist
Join our US Data team. We want curious minds who love fast execution and real impact. Kickstart your career in an environment that values practical results over theoretical perfection. You will work on real-world business challenges, learning from senior colleagues, and deploying machine learning solutions directly to production. We want a candidate with a “startup attitude”-someone who is energetic, eager to learn, and possesses a strong “get it done” personality. You are not afraid to ask questions, experiment rapidly, and iterate on solutions. Reporting directly to the Data Science Team Leader, you will collaborate with Machine Learning Engineers and Data Scientists both in the US and the UK. You will gain extensive hands-on experience across our cutting-edge, cloud-native Google Cloud Platform (GCP) and MLOps tech stack.
- Contributing actively to the full data science lifecycle: from data preparation, cleansing, and feature engineering, through to model training, evaluation, and documentation.
- Assisting in the building and testing of proof-of-concept models to solve business challenges in real-time.
- Helping design and analyze A/B tests and other operational experiments to measure the real-world impact of our models.
- Working closely with the Data Science Team Lead, Machine Learning Engineers, and Data Product Lead to understand business requirements and translate them into data insights.
- Proactively develop your skills in Python, SQL, GCP (Vertex AI), and MLOps methodologies, capitalizing on mentorship from senior team members.
- Prior internship, co-op, or personal project experience focusing on applied machine learning (required).
- Familiarity with Git version control and collaborative software development practices (required).
- Basic exposure to cloud platforms (GCP, AWS, or Azure) (required).
- High energy, curiosity, and a proactive approach to solving problems (required).
- You are highly motivated by seeing your work have an immediate impact on business outcomes (required).
- Solid proficiency in Python and familiarity with key data science libraries (Scikit-learn, Pandas, NumPy), as well as AI technologies deployed in a production environment (required).
- Good understanding of SQL and experience writing queries to retrieve and manipulate datasets (required).
- A solid understanding of core machine learning algorithms, statistical concepts, and data analysis techniques (required).
- Strong verbal and written communication skills; comfortable presenting findings and collaborating with remote and local team members (required).
- Bachelor’s or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, physics, or Engineering) or equivalent practical experience (e.g., intensive bootcamps combined with strong personal portfolios) (required).
- Compensation: USD 70000 - USD 85000 - yearly.
bet365 is one of the world's leading online gambling companies, founded in 2000 by Denise Coates CBE. The company employs over 9,000 people and serves more than 100 million customers in 27 languages, with a market-leading position built on its In-Play betting product. It offers betting across 96 sports and hundreds of thousands of streaming events, handling millions of requests and bets at peak times. Headquartered in Stoke-on-Trent, England, bet365 is known for its software innovation and continues to develop its online betting and gaming platform.
