Remote Data Scientist
Swish Analytics
π΅ $100k-$175k
πRemote - United States
Please let Swish Analytics know you found this job on JobsCollider. Thanks! π
Job highlights
Summary
Join Swish Analytics as a Soccer Data Scientist to develop machine learning and statistical models for sports betting products.
Requirements
- Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
- Demonstrated experience developing models at production scale for soccer or sports betting
- Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
- Minimum of 3+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting
- 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 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 Swishβs core algorithms for producing state-of-the-art sports betting products
- Develop contextualized feature sets using specific domain knowledge in soccer
- Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with 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 to stakeholders and other technical and non-technical partners
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