Data Engineer - Trading Analytics
San Francisco, CA
Swish Analytics
Sports betting & daily fantasy predictions, tools, analytics, projections & optimized lineups for NFL, MLB, NBA & NHL on FanDuel, DraftKings & Yahoo...Company Overview
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.
Job Description
Swish Analytics is seeking a Data Engineer to support our Trading Analytics team. The person in this role will ensure that client data is accurately ingested and reported to key stakeholders. They will work closely with the Trading team and Software Engineering team to troubleshoot client streams and monitor the accuracy of results in real-time. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Duties:
- Advance data engineering aspects of Trading Analytics, enabling faster and better trading decisions and reducing the reliance on manual reporting
- Lead Trading team and customer based reporting, as well as on-demand data needs for Swish.
- In conjunction with Trading Analytics Manager, the Data Engineer will develop impactful and accurate reports, dashboards, and other data visualizations.
- Maintain data integrity and ongoing quality of delivered reports.
- Identify data quality issues and work with Data Science, Data Engineering, and Software Engineering teams to resolve challenges.
- Integrate large, complex real-time datasets into new consumer and enterprise products.
- Develop production-level predictive analytics into enterprise-grade APIs.
- Contribute to the implementation of fully-automated sports data delivery frameworks.
Requirements:
- BS degree or higher in Computer Science, Data Science, Data Analytics or similar major
- Minimum of 1 year of experience writing production level code.
- Proficiency in Python (pandas, NumPy).
- Proficiency in SQL (preferably MySQL).
- Experience utilizing REST APIs.
- Experience in SQL database management, shema design, index structuring.
- Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS).
- Experience with web scraping and cleaning unstructured data.
- Knowledge of data science and machine learning concepts.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs AWS Computer Science Data Analytics Data quality Engineering Git Machine Learning Mathematics MySQL NumPy Pandas Python Shell scripting SQL Unstructured data
Perks/benefits: Startup environment
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