theScore, a wholly-owned subsidiary of PENN Entertainment, empowers millions of sports fans through its digital media and sports betting products. Its media app ‘theScore’ is one of the most popular in North America, delivering fans highly personalized live scores, news, stats, and betting information from their favorite teams, leagues, and players. theScore’s sports betting app ‘theScore Bet Sportsbook & Casino’ delivers an immersive and holistic mobile sports betting and iCasino experience. theScore Bet is currently live in the Company's home province of Ontario. theScore also creates and distributes innovative digital content through its web, social and esports platforms.
About The Work
We are looking for a talented and experienced Data Science Manager to join our team. We are looking for someone who is interested in leading the development of projects, testing the execution and delivery, and measuring the ultimate impact to our business. You will be responsible for leading and mentoring a team of data scientists who will build models which enhance personalization efforts, forecast key metrics, segment customer targets and automate solutions for internal teams and our online gaming customers.
Things our team will be working on:
- Recommendation engines: Data scientists can build recommendation engines to suggest bets to users based on their past betting history and other factors, such as their favorite teams and sports. This can help users to find bets that they are more likely to win and to increase the overall betting experience.
- Player clustering and classification: Data scientists can use clustering and classification algorithms to group players into different categories based on their betting behavior. This information can be used to tailor marketing and promotional campaigns to specific groups of players and to identify potential problem gamblers.
- A/B feature testing: Data scientists can use A/B feature testing to test different versions of the sportsbook website and app to see which ones perform better. This information can be used to improve the user experience and to increase the number of bets that are placed.
- Document classification and extraction: Data scientists can use natural language processing (NLP) techniques to classify and extract information from documents, such as news articles and social media posts. This information can be used to identify trends in the betting market, to identify potential fraud, and to generate insights for the sportsbook's traders.
- Sentiment analysis: Data scientists can use sentiment analysis to identify the sentiment of users on social media and other online platforms. This information can be used to understand public opinion about the sportsbook and to identify potential problems.
Responsibilities
- Conceive, plan and prioritize data projects with the Director of Data Science & Machine Learning.
- Setting the vision and strategy for the Data Science team.
- Developing and managing the team's budget.
- Hiring, training, and mentoring team members.
- Communicating with stakeholders across the organization about the Data Science team's work.
- Presenting the team's findings to both technical and non-technical audiences.
- Collaborating with Data Engineering, Business Intelligence, and other stakeholders to provide internal data services.
- Testing the performance of our products and features to guide the growth and development of the application.
Requirements
- University degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or related field.
- Experienced technical lead for the data science team, with experience mentoring team members.
- Experience in software engineering or operations, especially in a Dockerized development environment.
- 4+ years professional experience as a Senior Data Scientist with some management experience.
- A strong foundation in mathematics and statistics is essential.
- Proficiency in Python.
- Advanced knowledge in cloud computing across AWS, GCP, or Azure, with a preference for GCP.
- An understanding of software engineering principles and practices can be helpful in deploying data products in an enterprise environment.
- Curiosity and ability to convert complex problems into concrete requirements and build innovative solutions.
- Ability to communicate clearly, efficiently, and empathetically with technical and non-technical stakeholders.
What We Offer
- Competitive compensation package.
- Fun, relaxed work environment.
- Education and conference reimbursements.
- Parental leave top up.
- Opportunities for career progression and mentoring others.
theScore is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability or age.
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