Fanatics is building a leading global digital sports platform. The company ignites the passions of global sports fans and maximizes the presence and reach for hundreds of sports partners globally by offering innovative 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 over 900 sports properties, including major national and international professional sports leagues, teams, players associations, athletes, celebrities, colleges, and college conferences, and over 2,000 retail locations, including its Lids retail business stores. 

 

As a market leader with more than 18,000 employees, and hundreds of partners, suppliers, and vendors worldwide, we take responsibility for driving toward more ethical and sustainable practices. We are committed to building an inclusive Fanatics community, reflecting and representing society at every level of the business, including our employees, vendors, partners and fans. Fanatics is also dedicated to making a positive impact in the communities where we all live, work, and play through strategic philanthropic initiatives.

 

We are looking for senior-level Data Scientists to join our Data Engineering, Science, and Analytics team. Do you thrive at applying data science to solve business problems? As a data scientist, you will have ample opportunities to apply your data science skillset to unlock vast business opportunities by extracting key insights using a wide range of data sources, advanced statistical models, and machine learning algorithms and translating results into meaningful, goal-oriented business actions. Each day, you will be presented with a variety of new challenges and interesting projects that tap your interests and strengths.

Responsibilities:

• Collaborate with cross-functional partners in operations, finance, marketing, and engineering to understand business need and scope data science projects.
• Wrangle, process, cleanse, verify, and enrich data from different sources used for analysis.
• Help build data-informed business strategy and roadmaps.
• Translate business needs into data product requirements, evaluate technologies, and identify opportunities to innovate and improve our data science capabilities.
• Use creative problem-solving skills to analyze data and build statistical / machine learning models to help solve business problems from different perspectives.
• Work closely with data engineers to create services that can ingest and supply data to and from both internal and external sources and ensure data quality and timeliness.
• Lead the development of data visualization and dashboards to help the organization monitor performance, generate insights, and continuously improve user experience.
• Establish playbooks to drive process and consistent outcomes.
• Participating in the full life cycle of model development, which spans from business problem discovery, data discovery to model deployment and monitoring.

Qualifications:

• Master’s or Doctoral degree in Computer Science (with a focus on Deep Learning, Generative AI, Machine Learning, and Data Mining), Statistics, Econometrics, Physics, or other rigorous quantitative disciplines that require processing and modeling data at a complex and large scale.
• 6+ years of professional experience as a data scientist or an AI specialist.
• Proficient in Python, SQL, Spark, the associated Python and Spark packages commonly used by data scientists, and Deep Learning libraries, such as PyTorch.
• Proficient in wrangle and analyze data with complex relationships and time scale.
• Strong understanding of and practical experience in a wide range of machine learning algorithms and statistical modeling.
• Experience in using data visualization and dashboard tools.
• Working experience in cloud-native technology.
• Experience working with large structured and unstructured datasets stored in relational and NOSQL databases.
• Out of-the-box thinker and problem solver who can turn ambiguous business problems into clear data-driven solutions that deliver meaningful business impacts.
• Excellent organizational skills, verbal and written communication skills, and presentation skills.

• Proficient in other languages, such as R, used in data science.
• Basic knowledge of data engineering and MLOps.
• Certificates earned in data mining, machine learning, deep learning, statistical modeling, cloud computing, and data engineering.

$167,000 - $186,000 a year

The salary range for this position is $167,000-$186,000 which represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay, as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training.