Staff Data Scientist
Location: Remote Work

Job Description:

Location: Remote (U.S.)
Posted: February 1, 2025

About Fanatics Commerce:

Fanatics Commerce is transforming the sports merchandise industry. As the leading designer, manufacturer, and seller of licensed fan gear, jerseys, and lifestyle products, we cater to passionate fans of sports worldwide. With partnerships spanning across major leagues, teams, and sports organizations—including the NFL, NBA, MLB, MLS, and top international clubs like Manchester United and Paris Saint-Germain—we are at the heart of fan culture. From online shopping to stadium experiences, we are revolutionizing how fans interact with their favorite teams.

We are looking for a Staff Data Scientist to help shape the future of sports apparel sales by building and deploying impactful machine learning models to predict customer behavior and improve marketing strategies.


Your Role at Fanatics Commerce:

As a Staff Data Scientist in our Customer Marketing Science group, you will work on high-impact projects that shape our marketing strategies and drive sales of sports apparel for millions of customers. From predicting team preferences based on past behaviors to identifying customers likely to make a repeat purchase, your work will directly influence how we engage with fans and maximize their shopping experience.

Here’s what you’ll do:

???? Train & Deploy ML Models

  • Develop machine learning models for customer relationship management (CRM) to predict customer preferences, repeat purchases, and lifetime value.
  • Deploy these models into production to run at scale and ensure consistent impact.

???? Drive Insights with Exploratory Analysis

  • Conduct in-depth analysis to identify how we can transform complex business challenges into data-driven solutions.
  • Use insights to recommend actionable changes that enhance our marketing strategies.

???? End-to-End Project Leadership

  • Take the lead on data science projects from concept to execution.
  • Align business goals with science techniques, ensuring a seamless transition from ideas to actionable models.

???? Mentor and Guide Junior Data Scientists

  • Share your expertise by mentoring junior team members in data science techniques and best practices.
  • Lead by example, fostering a culture of collaboration and growth within the team.

What You Bring to the Table:

???? Qualifications & Experience:

  • 5+ years of experience as a data scientist or machine learning engineer.
  • Proven ability to mentor junior team members and guide them in their data science careers.
  • Proficiency in Python, R, or other data science languages.
  • Experience with customer segmentation, lifetime value models, and other marketing science use cases.
  • Strong command of machine learning techniques such as XGBoost, regressions, hyperparameter tuning, and feature selection.
  • At least one successful project where a model ran continuously in production (as an API or batch process).
  • Comfortable working with large, complex datasets that span multiple tables and sources.
  • Experience running data science tasks in cloud environments (AWS, GCP, Azure).

Why Join Fanatics Commerce?

???? Competitive Salary & Benefits

  • Salary Range: $196,000 - $235,000 based on experience and location.
  • Eligible for the Fanatics Commerce Annual Bonus Program and equity awards.

???? Impactful Work

  • Play a crucial role in improving how millions of fans engage with their favorite sports teams and apparel.
  • Be a part of high-impact marketing projects that directly influence business growth.

???? Company Culture

  • Fanatics Commerce thrives on BOLD Leadership Principles:
    • Build Championship Teams
    • Obsessed with Fans
    • Limitless Entrepreneurial Spirit
    • Determined and Relentless Mindset

Ready to Lead the Way?
If you’re passionate about sports, data science, and marketing, and ready to lead impactful projects, we want you on our team! Apply now and help us make the fan experience even more amazing with Fanatics Commerce!


Key Skills:

  • Staff Data Scientist