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Swish Analytics
Swish Analytics
11 – 50 Employees
H1B Visa SponsorConsultingGamblingMarketing
Swish Analytics develops machine-learning software and predictive data for the sports betting industry. Its B2B platform helps sportsbooks and fantasy platforms generate real-time odds across player props, team and match markets, pre-game forecasts, in-play events, parlays, bet builders, and micro-markets. The company also supports automated bet-lifecycle management, combining pricing models and scalable odds infrastructure to streamline how betting products are created and managed.
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Analytics Engineer (Python, Rust, SQL) — California Remote

Investigate real-time event systems and develop statistical metrics for Swish Analytics’ sports betting and fantasy data products. Use Python, Rust, SQL, and production data to explain system behavior and support reliable decisions.

USUnited StatesCACalifornia
$150,000 / year
RemoteFull-timeMiddleSeniorEnglish RequiredAnalytics Engineer
PythonRustSQL

Description

  • Trace incidents and requests through raw production data and systems to identify root causes and recommend solutions.
  • Develop and maintain statistically grounded metrics that track system health and performance over time.
  • Create clear, descriptive reports for stakeholders.
  • Improve shared frameworks and tools so investigations and measurement are more consistent and repeatable.
  • Work independently on ambiguous problems with incomplete initial scope.
  • Partner with data science, engineering, and trading teams when issues span organizational boundaries.
  • Analyze real-time, event-driven data to reconstruct and explain system behavior during live events.

Requirements

  • Bachelor’s degree in computer science, statistics, data science, or a related field.
  • At least four years of professional software engineering experience, including work on production systems.
  • At least two years of Python experience involving data extraction, wrangling, and analysis.
  • At least one year of production Rust experience.
  • Experience building and maintaining production software that handles real-world data, beyond prototypes, one-off scripts, or notebook analyses.
  • Advanced SQL skills and hands-on experience with raw or source data such as logs, event streams, and production tables.
  • Experience solving open-ended problems with limited initial direction.
  • Strong statistical and quantitative reasoning abilities.
  • Experience with event-driven or real-time data systems is preferred.
  • Experience in analytics engineering, applied statistics, or a combined data and software role is preferred.
  • Familiarity with sports, sports betting, or trading concepts is helpful but not required.

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