What are the responsibilities and job description for the Sports Data Analyst position at 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:
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
- 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
- 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