Soccer Data Scientist - EU at Swish Analytics

Malta

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€51,200 – €80,000Compensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Sports Analytics, Sports BettingIndustries

Requirements

Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
Demonstrated experience developing models at production scale for soccer or sports betting
Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
Minimum of 3+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting
Experience with relational SQL & Python
Experience with source control tools such as GitHub and related CI/CD processes
Experience working in AWS environments etc
Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions
Excellent communication skills to both technical and non-technical audiences

Responsibilities

Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products
Develop contextualized feature sets using specific domain knowledge in soccer
Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models
Strive to constantly improve model performance using insights from rigorous offline and online experimentation
Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts
Adhere to software engineering best practices and contribute to shared code repositories
Document modeling work and present to stakeholders and other technical and non-technical partners

Skills

Key technologies and capabilities for this role

Machine LearningStatistical ModelingFeature EngineeringModel DeploymentA/B TestingData AnalysisSoftware EngineeringSoccer Analytics

Questions & Answers

Common questions about this position

What is the salary range for the Soccer Data Scientist position?

The salary range is €51,200.00 - €80,000.00.

Is this position remote?

Yes, the position is fully remote.

What skills and experience are required for this role?

Requirements include a Master's degree in Data Analytics, Data Science, Computer Science or related field, 3+ years developing machine learning/statistical models for sports or betting, expertise in Probability Theory, Machine Learning, Statistics, experience with SQL, Python, GitHub, AWS, plus strong leadership and communication skills.

What is the company culture like at Swish Analytics?

The company seeks team-oriented individuals passionate about predictive data in a fast-paced, creative, continually-evolving environment that values technical excellence, while working in uncharted territory across industries.

What makes a strong candidate for this Soccer Data Scientist role?

Strong candidates have a Master's degree, proven production-scale modeling experience in soccer or sports betting, deep expertise in ML and statistics, hands-on skills in Python/SQL/AWS/Git, and demonstrated leadership with excellent communication.

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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