Junior Data Scientist

Company Description

We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages.

We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our global worldwide.

Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak.

Job Description

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.

The listed salary for this position is $70,000-$85,000 annually.

Qualifications

Prior internship, co-op, or personal project experience focusing on applied machine learning.

Familiarity with Git version control and collaborative software development practices.

Basic exposure to cloud platforms (GCP, AWS, or Azure).

High energy, curiosity, and a proactive approach to solving problems. You are highly motivated by seeing your work have an immediate impact on business outcomes.

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.

Good understanding of SQL and experience writing queries to retrieve and manipulate datasets.

A solid understanding of core machine learning algorithms, statistical concepts, and data analysis techniques.

Strong verbal and written communication skills; comfortable presenting findings and collaborating with remote and local team members.

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).

Additional Information

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.

bet365 provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.