Sports Data Analyst - Swish Analytics

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.

Duties:

Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues

Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data

Source origins of data inaccuracies through data pipeline dependencies and python code base

Define data validation tests to flag future game errors

Research accurate roster active statuses, primary positions and game participation

Validate data changes after logic updates

Production model feature deep dives to explain project market lines

Clearly document findings

Develop intimate familiarity with existing databases and construct metadata references

With guidance, support lead Data Scientists in feature development and model analysis

Requirements:

Bachelor's Degree in Computer Science, Data Science or similar major

Minimum of 1 year of experience in football data analysis

Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios

Data Extraction, Wrangling and Analysis in Python

Strong SQL querying skills

Attention to detail

Preferred:

Strong Python data management programming skills

Data Visualization experience with a user application like Streamlit

Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis

Exposure to the data science process and tech stack

Anomaly Detection Techniques

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 the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of backg