Paradise Media is a fast-growing performance marketing company behind some of the most successful affiliate and iGaming brands in the world. We run a global network of high-authority sites across casino, sports, and entertainment built on data, experimentation, and top-tier SEO.

We’re a private company with strong capital reserves and no outside investors, making us a stable, independent, and fast-moving place to grow your career. You’ll work directly with the CEO and leadership team, have a real voice in strategy, and see your ideas go live fast.

We’re scaling quickly to become one of the largest privately-owned companies in iGaming. A team where smart, driven people can have a massive impact and build something enduring.

About the role

As part of the Data and BI Team and reporting to the Lead Data Scientist, the chosen candidate will be responsible for developing, deploying, and maintaining machine learning solutions that support business objectives. This role is ideal for candidates with a strong background in data science, statistics, and applied machine learning, who are passionate about building scalable ML systems and driving data-informed decision-making.

Roles & Responsibilities: 

• Design, train, and deploy machine learning models for predictive analytics and optimization.
• Perform data exploration, cleaning, and feature engineering to prepare datasets for modeling.
• Collaborate with data scientists, analysts, and engineers to design end-to-end ML workflows.
• Conduct statistical analysis, hypothesis testing, and model evaluation to ensure robustness and accuracy.
• Implement best practices for ML lifecycle management, including monitoring, retraining, and performance optimization.
• Research and prototype advanced machine learning techniques to improve model effectiveness.

Requirements:

• 1 year experience working in a Data Team or Data Analyst Role or ML engineer in a Data Science team
• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• Solid understanding of statistical modelling, probability, and machine learning algorithms (supervised and unsupervised).
• Proficiency in Python with experience using ML and data libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Strong knowledge of SQL and experience working with structured datasets.
• Hands-on experience in building, evaluating, and deploying ML models into production environments.
• Strong problem-solving, analytical, and quantitative skills.
• Effective communication skills and ability to work collaboratively in cross-functional teams.

Our Benefits:

We offer a competitive salary, and the opportunity to work with a talented and passionate team in a fast-paced, dynamic environment.