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About the Role

Swish Analytics is building the next generation of predictive sports analytics data products. We are seeking team-oriented individuals passionate about accurate, real-time data to execute in a fast-paced, creative, and evolving environment. This role involves analyzing factor usage, designing tests for simulation changes, and analyzing market data to automate Contrarian Signals. The position will grow into building models for factor optimization as the company expands to new sports.

Responsibilities

Analyze factor usage data, including downstream effects and impact on simulation outputs, to generate actionable insights.
Design and implement tests to detect unexpected simulation changes caused by factor modifications.
Develop and enhance machine learning and statistical models for core algorithms, progressing to factor-optimization modeling for new sports.
Create contextualized feature sets leveraging sports-specific domain knowledge.
Participate in all phases of model development, from concept to deployment, collaborating with data engineering and product teams.
Continuously improve model performance through rigorous offline and online experimentation.
Evaluate model performance, identify limitations, and guide future development efforts.
Document work and present findings clearly to both technical and non-technical stakeholders.

Requirements

Bachelor's degree in Data Science, Statistics, Computer Science, Applied Math, or a related technical field; Master's degree strongly preferred.
Minimum of 4 years of experience developing and deploying effective machine learning and/or statistical models within sports analytics or sports betting.
Solid understanding of Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods.
Exceptional analytical and problem-solving skills with a proven ability to learn quickly in new areas.
Proficiency in Python and relational SQL.
Experience with source control systems like GitHub and associated CI/CD processes.
Experience working within AWS environments.
Ability to collaborate effectively across teams on complex, ambiguous problems.
Clear communication skills for both technical and non-technical audiences.

Skills

Python
SQL
GitHub
CI/CD
AWS
Probability Theory
Machine Learning
Inferential Statistics
Bayesian Statistics
Markov Chain Monte Carlo methods

Location

Remote (USA)
Remote (Canada)

Work Type

Remote
Full-time

Experience Level

4+ years

Education Level

Bachelor's degree
Master's degree preferred

Salary/Compensations

Starting at $160,000 - DOE

About the Company

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.
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.

Equal Opportunity

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law.
The position responsibilities are not limited to those outlined above and are subject to change.
At the employer's discretion, this position may require successful completion of background and reference checks.