Staff Data Scientist - Digital Experiences
San Mateo, CA, United States
Applications have closed
Fanatics
Fanatics.com is the ultimate sports apparel and Fan Gear Store, featuring football Jerseys, T-shirts, Hats, Collectibles and merchandise for fans of the NFL, MLB, NBA, NHL, Soccer, and College.Staff Data Scientist, Digital Experiences
Company Overview
Fanatics is a leading global digital sports platform, complete with offerings that excite fans and maximize the reach and presence for partners across the entire sports ecosystem. Come help us build a company the world has never seen before! We are first and foremost a technology company. We build innovative fan experiences through highly analytical, forward thinking, and open-minded collaboration. At Fanatics, we are passionate about leveraging data to drive growth and operational efficiencies. We firmly believe in putting data at the forefront of delivering an engaging experience for our sports fans!
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.
Summary
If you excel at using data science to tackle business issues, this may be the perfect role for you! As part of our team, you’ll get the chance to apply your data science skills to generate business growth.
You’ll be expected to build & deploy predictive models in the field of AI and Machine Learning, with the potential to lead the work of others to deliver complex models, analytical projects and solve business problems, and act as a mentor and thought leader for the team. Dive into complex data sets to analyze trends and identify opportunities for improvement to help drive decision-making. You’ll extract vital insights from diverse data sources, employ machine learning algorithms, and apply advanced statistical models. Your findings will be translated into business actions.
Responsibilities
- Partner with colleagues from engineering, product, marketing, and finance to understand business needs and scope data science projects
- Train, build and deploy machine learning models for gaining a deeper understanding of our customers
- Convert data requirements into data product requirements, evaluate technologies, and identify opportunities to innovate and improve our data science capabilities.
- Apply innovative problem-solving skills to dissect data and build machine learning / statistical models to solve business problems from different perspectives.
- Participating in the full life cycle of model development, which spans from business problem discovery, data discovery to model deployment and insights
Qualifications
- Master’s or Doctoral degree in Computer Science (with a focus on AI, Machine Learning, Data Mining), Statistics, Econometrics, Physics, or other quantitative disciplines that require processing and modeling data at a large scale.
- 5+ years of professional experience as a senior data scientist
- 2+ years experience as a tech lead within a data organization
- Proficient in Python, SQL, Spark, the associated Python and Spark packages commonly used by data scientists, and Deep Learning libraries, such as PyTorch
- Strong understanding of and practical experience in a wide range of machine learning algorithms and statistical models.
- Experience in using large & complex datasets spanning many tables
- 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.
Physical Requirements
Ability to work in-office a minimum of three days a week.
The expected salary range for this role is $180,000 - $225,000. This is based on job-related knowledge, skills, and experience. This role is also eligible for the Fanatics Commerce annual bonus program and an equity award. This salary range is listed in USD and will be determined in part by a successful candidate’s geographic location.
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.Tags: Computer Science Data Mining Deep Learning Econometrics Engineering Excel Finance Machine Learning ML models Model deployment Physics Python PyTorch Spark SQL Statistics
Perks/benefits: Career development Conferences Equity / stock options Salary bonus
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