Sr. Data Scientist

3+ months agoVancouver, Canada

About Skillz:

Skillz is the leading mobile games platform connecting players in fair, fun, and meaningful competition. 

The gaming industry is larger than movies, music, and books, with more than 2.7 billion gamers playing monthly and 10 million developers worldwide. Mobile is the fastest-growing segment of the gaming market, expected to increase from $86 billion last year to $161 billion in 2025. 

As the first publicly-traded (NYSE: SKLZ) mobile esports platform, Skillz has pioneered the future of the gaming industry. The Skillz platform helps developers build multi-million dollar franchises by enabling social competition in their games. Leveraging its patented technology, Skillz hosts billions of casual esports tournaments for millions of mobile players worldwide, and distributes millions in prizes each month.

Through its philanthropic initiatives, Skillz has harnessed the power of its platform to transform the way nonprofits engage with donors, enabling anyone with a mobile device to support causes such as the American Red Cross, Susan G. Komen, American Cancer Society, and NAACP by playing in Skillz tournaments.

Skillz has also earned recognition as one of San Francisco Business Times’ Best Places to Work, Fast Company’s Most Innovative Companies,’s Best Companies for Women to Advance, a two-time winner of CNBC’s Disruptor 50, one of Forbes’ Next Billion-Dollar Startups, and the #1 fastest-growing company in America on the Inc. 5000.

Who We Are Looking For:

You are ready to take the next step in your Data Science career - to a fast-moving, successful company building out their world class competitive platform! You are passionate about data and finding patterns and insights that others often overlook. You are looking to have a big impact on a small team. You are oozing with curiosity and want to find new and novel ways to leverage your current skill set. You are an excellent communicator and know that you grow faster from being able to mentor others.


What You Will Do:

  • Implement models for a variety of use cases, ranging from player matching to forecasting to fraud and cheat detection
  • Plan and estimate research projects for the team on a weekly, monthly, and quarterly cadence
  • Communicate your findings to a larger business audience
  • Mentor more junior team members and be a voice of statistical rigor across the entire organization as you grow your leadership skills
  • Collaborate with other engineering teams to have your algorithms implemented in production


Your Skillz:

Basic Qualifications

  • Experience delivering ML projects end to end in an enterprise setting, including articulating the business use case; cleaning and exploring the data; and building, testing, and deploying predictive models
  • Pragmatic thinker whose primary aim is to build effective solutions that positively impact the business
  • Demonstrated experience delivering value to business stakeholders using Data Science techniques
  • Solid, applied understanding of both Machine Learning and Statistics along with a desire to deepen this understanding
  • Strong cross-functional, communication skills that help simplify and move complex problems forward with business partners 
  • 5+ years programming experience (Python, R or any other relevant language) 
  • 5+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
  • 3+ years of experience using SQL 
  • Excellent at breaking down complicated tasks and delegating the work to others while still ensuring quality
  • Experience mentoring more junior team members
  • Comfortable working in a fast paced, highly collaborative, dynamic work environment
  • M.S. in a quantitative field


  • Ph.D. in a quantitative field 
  • Experience in AWS or some other cloud provider
  • Experience with Spark and large-scale data analysis
  • Hands on experience building models with deep learning frameworks


Skillz embraces diversity and is proud to be an equal opportunity employer. As part of our commitment to diversifying our workforce, we do not discriminate on the basis of age, race, sex, gender, gender identity, color, religion, national origin, sexual orientation, marital status, citizenship, veteran status, or disability status, and we operate in compliance with the San Francisco Fair Chance Ordinance.