Swish Analytics Logo

Swish Analytics

Analytics Engineer

Posted 6 Days Ago
In-Office or Remote
Hiring Remotely in San Francisco, CA, USA
Mid level
In-Office or Remote
Hiring Remotely in San Francisco, CA, USA
Mid level
Investigate production incidents using raw real-time data, identify root causes, and recommend resolutions. Build statistical system-health metrics, descriptive reports, and repeatable investigation tooling. Analyze event-driven systems during live sports events, work independently on ambiguous problems, and collaborate with data science, engineering, and trading teams. Develop and maintain production software using Python and Rust.
The summary above was generated by AI

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.

About the Team

The Suspensions team is responsible for the framework, monitoring, and analysis behind how markets are suspended and resumed — from the moment a market opens pregame through live gameplay to close. A few examples of what the team owns: real-time event processing that triggers suspensions off live game state, monitoring and alerting on suspension/resumption latency and failures, tooling that reconstructs and audits what happened during a specific suspension event, and rate/downtime metrics that describe how well suspension coverage is performing across sports and markets. The team works directly in Python and Rust across this stack, and partners closely with data science, trading, and engineering teams whose systems intersect with suspension logic.

Responsibilities

  • Investigate individual incidents and requests end-to-end, working directly with raw production data and systems to determine root cause and recommend resolution

  • Build and maintain metrics that measure system health and performance over time, using statistical methods as the core analytical approach, while also producing clear descriptive reporting for stakeholders

  • Contribute directly to the team's core framework and tooling, making investigation and measurement work more repeatable and less bespoke over time

  • Operate independently on ambiguous, partially-scoped problems, identifying the right cross-functional partners (data science, engineering, trading) when a problem crosses 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 — figuring out the right questions to ask, who else needs to be involved, and driving the work to a conclusion without needing the problem pre-scoped for you

  • Genuine statistical/quantitative reasoning skills — comfortable building rigorous, defensible measures of system behavior

Preferred

  • Experience with event-driven or real-time data systems (e.g., Kafka or comparable)

  • Background in analytics engineering, applied statistics, or a hybrid data/software role

  • Exposure to sports, sports betting, or trading concepts (helpful, not required)

Base salary: Starting at $150,000 base to DOE

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 background and reference checks.
HQ

Swish Analytics San Francisco, California, USA Office

San Francisco, CA, United States

Similar Jobs

6 Days Ago
Remote or Hybrid
CA, USA
100K-145K Annually
Senior level
100K-145K Annually
Senior level
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Manage data center financial operations through budgeting, variance analysis, financial modeling, month-end close reporting, cost-saving initiatives, and strategic analysis. The role requires data warehousing and modeling expertise, hardware and asset-management understanding, process improvement, automation, and effective communication with leadership and cross-functional partners.
Top Skills: Artificial IntelligenceData ModelingData WarehousingExcelMicrosoft Powerpoint
Yesterday
Remote
United States
140K-175K Annually
Mid level
140K-175K Annually
Mid level
Information Technology • Software • Database
Build and expand the company’s analytics data stack using Looker, LookML, dbt, BigQuery, and Airbyte. Develop data models, integrate multiple business systems, create KPI dashboards, and analyze product usage, customer health, adoption, and revenue data. The role empowers business teams with self-service analytics, actionable insights, and data-informed decision-making while developing a strong understanding of business metrics.
Top Skills: AirbyteBigQueryClickhouseDbtLookerLookmlMetronomeSalesforceSegmentStripe
3 Days Ago
Remote
USA
200K-250K Annually
Senior level
200K-250K Annually
Senior level
Information Technology • Software
Own the customer experience data foundation by designing dbt models, pipelines, data quality tests, documentation, semantic layers, dashboards, and self-service datasets. Integrate support, KYC, withdrawal, CRM, workforce management, and market resolution data into the cloud warehouse. Identify recurring support issues, communicate findings to stakeholders, and partner with data engineering on infrastructure and governance.
Top Skills: AirbyteBigQueryDbtFivetranPythonRedshiftSnowflakeSQL

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account