Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.
Fanatics Betting and Gaming is seeking a Staff Data Scientist to support our Data Science, Engineering and Analytics (DSEA) Team. Your role will involve applying data science and machine learning techniques to solve highly complex problems in the area of trading intelligence and sports betting. This role will require growing our analytics operations, working with stakeholders, adapting to changes based on customer feedback, the ability to try multiple solutions and ultimately be flexible in a very data rich and complex environment. You will work with an amazing team of data scientists and engineers to both lead and execute cutting edge work as FBG continues to push the boundaries of sports betting and iCasino.
Responsibilities
Duties and responsibilities may include:
● Design and implement data science techniques to complex problems from end to end
● Lead/guide other data scientists on various projects
● Work directly with stakeholders to understand requirements, provide details on feasibility, assess tradeoffs and present results in clear and concise manner
● Be flexible and adaptive. Be able to manage when roadblocks arise and projects shift priorities
● Collaborate with machine learning engineers, data engineers and quantitative analysts to implement long term and scalable solutions
● Communicate regularly with internal stakeholders, executive leadership, engineering, product and more
● Lead code/peer reviews to ensure high quality of work is implemented and “teach” where appropriate
● Develop and communicate standards and procedures for the data science team
● Mentor and coach other data scientists by providing leadership and expertise
● Participate in an on-call rotation when needed to troubleshoot various data science and machine learning issues
● Must be open to occasional travel to Fanatics Betting & Gaming offices and other locations for conferences, meetings and team-building events
● Remain current on the latest techniques in data science - especially those related to AI
Qualifications
● 7+ years of experience implementing data science or machine learning techniques to complex problems from start to finish
● Demonstrated understanding of a broad range of mathematical/statistical techniques
● Excellent analytical and problem solving skills
● Strong strategic thinking, written and verbal communication, and resource prioritization skills
● Understanding of sports betting terminology and strategies
● Proficiency in Python and SQL to work with large datasets
● An agile mindset with a desire to work in a fast-paced environment
● Able to effectively work cross-functionally within an enterprise environment
If you possess some of these skills but not all of them, we still encourage you to apply!
*Salary Range: $148,000 to $294,000 (actual salary will be determined in part by a successful candidate’s geographic location) The expected salary range for this role is based on job-related knowledge, skills, and experience. *Salary range is listed in USD; actual salary will vary based on location.