Data Scientist

Summary

Join Swish Analytics, a sports analytics startup, as a Data Scientist on the Trading Analytics team. You will play a crucial role in developing and improving machine learning and statistical models for state-of-the-art sports betting products. Responsibilities include creating algorithms for automated trading suggestions, contributing to all stages of model development, and rigorously analyzing model performance. You will collaborate with various teams and present findings to stakeholders. This position requires a Master's degree in a related field, significant experience in data science and financial risk management modeling, and expertise in statistical and machine learning techniques. A competitive base salary is offered.

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

Responsibilities

• 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

Benefits

Base salary: $101,500 - 141,500