Data Scientist

Fliff unpacks sports gaming into social, free-to-play games for all types of sports fans. We've built a social sports gaming experience that allows users to compete for leaderboard positioning, to achieve badges and build their status within the game.
We are pioneering play-for-fun sports gaming, with our flagship social sportsbook experience that includes sweepstakes promotions and loyalty rewards. We provide sports fans with fun, engaging, and free-to-play alternatives to real money gaming.
We are seeking a skilled and experienced Data Scientist to join our team. You will be responsible for analyzing large datasets, developing predictive models, and providing insights that drive business decisions, reporting directly to the executive team and company stakeholders.
The ideal candidate should be able to work independently and collaborate with cross-functional teams to deliver high-quality work in a fast-paced environment. Responsibilities:

• Conduct data analysis and modeling to identify trends, patterns, and insights that can be used to improve our platform.
• Develop predictive models and algorithms that can forecast outcomes for sports events and improve the accuracy of our predictions.
• Work closely with the product and engineering teams to integrate models and algorithms into our platform.
• Collaborate with other data scientists, analysts, and business stakeholders to ensure that our models and algorithms are accurate, reliable, and scalable.
• Monitor the performance of our models and algorithms and continuously improve them based on feedback and new data.

Requirements:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• Preferably at least 2-3 years of experience in data science, ideally in the sports gaming industry.
• Passion for sports and sports gaming.
• Strong programming skills in Python and experience working with libraries such as Pandas, NumPy, and Scikit-learn.
• Knowledge of SQL and experience working with databases and data warehouses.
• Experience with machine learning algorithms and statistical models, including supervised and unsupervised learning, regression, classification, and clustering.
• Strong problem-solving and analytical skills, with the ability to think creatively and outside the box.
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

Benefits:

• Top tier compensation + benefits package
• Flexibility to work remotely
• Opportunity for professional growth in a dynamic and international environment
• Informal, friendly and knowledge-sharing environment
• An interesting and challenging job that allows you to explore paths to creating successful software solutions