[Remote] Staff Software Engineer at Swish Analytics

San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Sports Analytics, Betting, Fantasy Sports, Data & Analytics, Software DevelopmentIndustries

Skills

Key technologies and capabilities for this role

MicroservicesAPIsKafkaKubernetesSDKsCLIsDatabase optimizationCloud cost optimizationArchitectural designHigh-traffic API managementNetworking topologyCode reviewPerformance optimizationDistributed data handling

Questions & Answers

Common questions about this position

What is the salary for this Staff Software Engineer position?

The salary starts at $140,000.

Is this a remote position?

Yes, this is a fully remote position.

What skills are required for this role?

Candidates need 8+ years of production software engineering and technical leadership experience, hands-on experience with NodeJS & Python, and databases (both relational and non-relational). Strong communication skills and a BS or higher in CS/CE/SE or relevant experience are also required.

What is the company culture like at Swish Analytics?

The company fosters a fast-paced, creative, and continually-evolving environment that values team-oriented individuals passionate about accurate predictive real-time data, technical excellence, and tackling unique challenges in uncharted territory.

What makes a strong candidate for this Staff Software Engineer role?

A strong candidate has 8+ years of experience including technical leadership, hands-on work with NodeJS, Python, and databases, plus a passion for reliability, high availability, automation, observability, and global scale, along with strong communication skills.

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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