Job Description

Quantitative Researcher, Baseball

Level: Experienced

Time Type: Full-Time

Compensation: $90,000 - $150,000 base salary + bonus + benefits

Location: San Francisco, CA (On-Site)

Start: Immediately

Cleat Street is a sports analytics company that leverages proprietary technologies in sports prediction markets. Our mission is to be the most innovative sports analytics company in the world. We want to share this expertise with our customers so they can make smarter betting decisions. Learn more at cleatstreet.com .

What We Are Looking For

Cleat Street is looking for an experienced analyst to build some of the most innovative predictive sports models in the world. Professional experience within the fields of predictive sports analytics, applied statistics and probabilistic modeling or financial and economic theory is particularly relevant for this position.

In joining Cleat Street, you will be given the opportunity to develop best-in-class game and player-level predictions. Your prediction models will be directly monetized through our team of experienced traders. The ideal candidate will appreciate the real-time performance feedback loop unique to sports betting and embraces our core values of excellence, transparency, and innovation.

Role and Responsibilities

The person in this role will work with the director of quantitative research in the development of proprietary predictive models for the MLB. This will include:

• Analyzing and interpreting a wide range of sports datasets
• Researching, building, testing, and deploying statistical and/or machine learning models
• Understanding the variance in sporting event outcomes
• Digesting and interpreting real-time market data to inform key forecast assumptions
• Educating colleagues on latest statistical and data processing techniques
• Communicating research findings to key stakeholders across the organization

Requirements

• Must love sports
• 1-5 years of professional experience in sports analytics, statistical analysis or financial asset valuation
• Understanding of typical baseball data structures, plus knowledge of current baseball research and traditional baseball statistics and strategy
• Demonstrated experience with statistical software (e.g. R, Python) and database querying (SQL)
• A naturally inquisitive and problem-solving mindset
• Excellent verbal and written communication skills, including ability to clearly communicate complex information

Preferred Qualifications

• Experience in Bayesian statistics and a variety of machine learning frameworks
• Prior experience analyzing baseball data for the purpose of predicting game/event outcomes (Sabermetric analysis, fantasy sports, sports betting)

Compensation and Benefits

• $90,000 - $150,000 with up to 50% bonus target
• Competitive 401k plan
• Medical, dental, and vision healthcare coverage 
• Unlimited PTO
• Monthly stipend for attending sporting events
• Free lunch daily

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