We’re looking for a hands-on Data Scientist to join as the first hire in our data science function, reporting directly to the Back-End Manager. This is a high-impact role where you’ll own the full lifecycle of projects - from concept through deployment - and set the technical and analytical foundations for future growth. You’ll develop advanced predictive models for sports forecasting and ad-tech optimization, directly influencing product decisions and revenue outcomes.
About Sidelines
Sidelines Group is one of the fastest-growing sports betting and iGaming affiliate companies in the industry, specializing in experience-driven technology. We’re looking for employees who are ambitious, willingly take ownership, and execute effectively — all to power the company forward
What will you do?
Full Ownership of Data Science Projects - Lead initiatives end-to-end: problem definition, data gathering, model development, deployment, monitoring, and iteration.
Sports Forecasting Models - Design and train statistical and machine learning models for predicting sports outcomes, player performance, and betting-related probabilities.
Ad-Tech Optimization - Build predictive and prescriptive models to improve user targeting, click-through rates, conversion probabilities, and ad inventory value.
Innovation & Research - Explore emerging ML/AI techniques in sports analytics, recommendation systems, and bidding optimization; translate findings into actionable solutions.
Visualization & Communication - Present results through intuitive dashboards, visualizations, and clear storytelling to both technical and non-technical stakeholders.
Cross-Team Collaboration - Partner with engineering, product, and business teams to identify opportunities, prioritize efforts, and deliver measurable impact.
What will you bring to the table?
BSc in Data Science (preferred) or in Computer Science/Software Engineering with a strong academic foundation in machine learning - Mandatory.
3+ years of experience in a Data Science role
Strong statistical and mathematical foundations (probability theory, regression, linear algebra, time-series analysis).
Proven expertise in Python with data science/ML libraries (Pandas, NumPy, Scikit-learn, LightGBM, XGBoost, TensorFlow/PyTorch) and OOP principles.
Experience writing and optimizing SQL queries.
Demonstrated ability to take models from notebook to production.
Experience with BigQuery - advantage.
Background in sports analytics or ad-tech - strong advantage.
Master’s degree with thesis in a quantitative discipline - advantage.