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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 Fast Company’s Best Workplaces for Innovators, San Francisco Business Times’ Best Places to Work, Parity.org’s Best Companies for Women to Advance, Fast Company’s Most Innovative Companies, 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.
What You'll Do
Research, design, and implement algorithms and pipelines for solving optimization and machine learning problems, e.g.
- User response prediction, CTR/CVR estimation
- Bid landscape forecasting from censored data
- Bidding and budget pacing strategies
- Fraud and anomaly detection
- Read relevant research and apply learnings to the problem domain
- Analyze system performance relative to various key metrics and establish a framework for fast iterative development
Required skills
- Proven track record in one of the following machine learning domains: recommender systems, Bayesian inference, latent variable models, neural networks, deep learning
- Strong working knowledge of machine learning, data modeling, and visualization in Python using the SciPy stack
- Experience with deploying machine learning models to production systems
- Experience with databases and SQL
- Good understanding of probability and statistics
- Good understanding of numerical optimization algorithms, convergence, stochastic optimization methods
Nice to have
- Experience with RTB (real-time bidding) or other computational advertising problems
- Experience with Rust, C++, C#, Java, or Scala
- Experience with data warehousing systems and MPP databases
- Working knowledge of auction and game theory
- Familiarity with network and system administration of high throughput/high load environments
Education
- Bachelor's in Mathematics, Physics, Computer Science, or another technical field
- Master’s or Ph.D. preferred
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 .