€75,000 – €85,000Compensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Sports Analytics, Data & Analytics, Betting, Fantasy SportsIndustries

Position Overview

  • Location Type: Remote
  • Employment Type: Full-time
  • Salary: €75,000 - €85,000

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 enterprise clients.

Requirements

  • 4+ years of experience working in a DevOps or DevSecOps role
  • 4+ years building within AWS, including EKS, EC2, RDS, and other common AWS services using Terraform, Terragrunt or similar technologies
  • 4+ years building CICD pipelines with Github Actions, Jenkins and ArgoCD
  • 4+ years of experience managing, provisioning and maintaining distributed systems with containerization tools, including Kubernetes, Docker, Helm
  • 2+ years of Python or Go experience
  • Deep understanding of distributed systems including storage, networking, and security
  • Previous SRE or DevOps experience in managing customer-facing systems in a 24/7 environment
  • Experience with machine learning pipelines

Responsibilities

  • Develop, maintain, and implement Kubernetes clusters at scale that are ready for heavy/spiky ML workloads
  • Work closely with Data Science and Data Engineering teams to implement, optimize, and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages
  • Help Data Science and Data Engineering develop and implement specialized infrastructure to deliver tools/software to improve the reliability and scalability of services
  • Pioneer, implement, and enforce best practices for software deployment and code management
  • Monitor the system and respond to incidents to maintain system SLO/SLA, review and follow up production incidents

Preferred Qualifications

  • Experience with ML Ops or similar
  • Knowledge in advanced statistical methods

Company Information

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.

Skills

AWS
EKS
EC2
RDS
Terraform
Terragrunt
Github Actions
Jenkins
ArgoCD
Kubernetes
Docker
Helm
Python
Go
Distributed Systems
Networking
Security
SRE
Machine Learning Pipelines

Swish Analytics

Sports analytics and optimization tools provider

About Swish Analytics

Swish Analytics specializes in sports analytics and optimization tools for daily fantasy sports and sports betting, focusing on major U.S. leagues like the NFL, MLB, NBA, and NHL. The company uses an advanced machine learning system to analyze large datasets, providing accurate sports predictions and optimized lineups. This helps users, including individual bettors and professional operators, make informed decisions about their bets and fantasy picks. Swish Analytics differentiates itself by being an Authorized MLB Data Distributor, establishing trust in the sports betting community. Operating on a subscription-based model, users can access various levels of tools and analytics, starting with a free trial. The goal of Swish Analytics is to maximize return on investment for clients by identifying the best bets and balancing risk and reward for long-term success.

San Francisco, CaliforniaHeadquarters
2014Year Founded
$6.5MTotal Funding
EARLY_VCCompany Stage
Fintech, AI & Machine Learning, Financial ServicesIndustries
51-200Employees

Benefits

Remote Work Options

Risks

Increased competition from AI-driven startups could erode Swish Analytics' market share.
Consumer privacy concerns may impact Swish Analytics' data collection practices.
Potential regulation of sports betting advertising could affect Swish Analytics' revenue streams.

Differentiation

Swish Analytics uses proprietary algorithms for accurate sports predictions and optimized lineups.
The company is an Authorized MLB Data Distributor, enhancing its credibility in sports betting.
Swish Analytics offers a subscription model with free trials, attracting diverse user segments.

Upsides

Increased legalization of sports betting in the U.S. expands Swish Analytics' market opportunities.
The rise of AI-driven personalized betting experiences aligns with Swish Analytics' machine learning expertise.
Growing interest in micro-betting offers Swish Analytics a chance to expand its offerings.

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