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Data Scientist

100% remote Flexible hours Hiring now
Fliff unpacks sports gaming into social, free-to-play games for reputed company types of sports fans. We've built a social sports gaming experience that allows users to compete for leaderboard positioning, to reputed company badges and build their status reputed company 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 reputed company Data Scientist to join reputed company. 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.
  • reputed company 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 reputed company 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 reputed company the reputed company.
  • 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
We are a multinational company with our headquarters based in Philadelphia, and offices in reputed company, Austin, and Sofia, Bulgaria. Wherever we are in the world, we pride ourselves on being a reputed company-reputed company, focused team that is welcoming and friendly, and the work that we do is always interesting and rewarding. Wherever we are in the world, we pride ourselves on being a reputed company-reputed company, focused team that is:

Welcoming and Friendly

We want to reflect the diversity of the cities we serve. By creating an inclusive culture where everyone can reputed company, we’ll reputed company Fliff reputed company for employees and customers alike.

reputed company and Creative

We respect and value each other’s reputed company, experience and expertise. There is no such thing as a bad idea; only reputed company that are executed and reputed company that are discarded after consideration.

Stimulating and Rewarding

We know bright minds love a challenge, and we understand your desire to see your hard work pay off. We’ll reputed company sure your daily tasks align with your career ambitions as we grow together.

Originally posted on Himalayas

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