Data Scientist - Trading Analytics

2 days ago

🇺🇸 United States – Remote

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

💵 $101.5k - $141.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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Swish Analytics

WebsiteLinkedInAll Job Openings

Sports Analytics • sports betting • gambling

11 - 50 employees

🎲 Gambling

🎮 Gaming

⚽ Sports

💰 $6.9M Series B on 2019-05

Description

• Company Description • Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients. • Job Description • Swish Analytics is seeking a Data Scientist to join our Trading Analytics team! Data Science is at the core of our business, and Trading Analytics provides the data, the metrics, and the tools enabling Swish to make informed decisions about business development and priorities. We’re hiring a Data Scientist to support our Analysis and Trading Tools development efforts. • Duties: • Ideate, develop, and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products. • Develop algorithms to provide automated trading suggestions that maximize margin and minimize risk. • Contribute to all stages of model development, from creating proof-of-concepts and beta testing to partnering with data science, data engineering, and product teams to deploy new models. • Strive to constantly improve model performance using insights from rigorous offline and online experimentation. • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts. • Adhere to software engineering best practices and contribute to shared code repositories. • Document modeling work and present it to stakeholders and other technical and non-technical partners.

Requirements

• Master's degree in Data Analytics, Data Science, Computer Science, or related technical subject area; Master's degree highly preferred • Prior Data Science or Data Analytics experience in financial risk management modeling (sports betting, hedge fund management, options trading, securities trading, etc) • Understanding of the sports betting marketplace or experience analyzing sports data • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods • 4+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs • Experience with relational SQL & Python • Experience with source control tools such as GitHub and related CI/CD processes • Experience working in AWS environments etc • Proven track record of strong leadership skills. Has shown the ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions • Excellent communication skills to both technical and non-technical audiences