Analytics Engineer

🕒 September 28

🏄 California – Remote

🏄 California – Remote

💵 $150k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Analytics Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Swish Analytics

WebsiteLinkedInAll Job Openings

11 - 50 employees

🎲 Gambling

🎮 Gaming

⚽ Sports

💰 $6.9M Series B on 2019-05

Gambling • Gaming • Sports

Swish Analytics is a company that specializes in machine learning for US sports betting and fantasy sports. They deliver accurate, algorithm-driven predictions and tools to help improve betting strategies across major sports leagues such as the NBA, NFL, MLB, and NHL. Swish Analytics offers tools like lineup optimizers for daily fantasy sports and is an Authorized MLB Data Distributor to U. S. sports betting operators. Their team consists of data scientists, machine-learning engineers, and developers dedicated to providing powerful analytics and innovative solutions for the sports betting and gaming industry.

📋 Description

• Investigate individual incidents and requests end-to-end using raw production data and systems to determine root cause and recommend resolution • Build and maintain metrics measuring system health and performance over time using statistical methods • Produce clear descriptive reporting for stakeholders • Contribute to the team's core framework and tooling to make investigation and measurement more repeatable • Operate independently on ambiguous, partially-scoped problems • Identify and collaborate with data science, engineering, and trading partners when problems cross team boundaries • Work with 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 similar major • Minimum of 4 years of professional software engineering experience, including production systems • Minimum of 2 years of experience with Python, including data extraction, wrangling, and analysis • Minimum of 1 year of experience with Rust in a production environment • Experience building and maintaining software that runs in production against real-world data — not just prototypes, one-off scripts, or notebook-based analysis • Strong SQL skills and direct experience working with raw/source data (logs, event streams, production tables) • Experience taking on open-ended problems with limited upfront direction • Genuine statistical/quantitative reasoning skills • Experience with event-driven or real-time data systems (preferred) • Background in analytics engineering, applied statistics, or a hybrid data/software role (preferred) • Exposure to sports, sports betting, or trading concepts (helpful, not required)

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