Best Remote Job: Swish Analytics Seeks Senior Basketball Data Scientist – $175K Max Salary

Swish Analytics Opens Remote Roles for Senior Basketball Data Scientists: Salary Up to $175K Annually

Swish Analytics, a fast-rising name in the field of predictive sports analytics, is hiring experienced professionals to join its remote team as Senior Basketball Data Scientists. This new hiring initiative comes as the company continues to expand its product line in the competitive sports betting and fantasy sports market. For data scientists with a passion for basketball, this role offers a rare opportunity to work on impactful, production-level sports models used by real-time bettors and fantasy enthusiasts.

Swish Analytics is accepting applications from qualified candidates based anywhere in the United States, offering a fully remote work setup with a generous annual salary range of $120,000 to $175,000, depending on qualifications and experience level.

Data Science at the Core of a Sports Tech Powerhouse

From courtside events to backend algorithms, Swish Analytics connects real-world basketball with data science to power smarter decisions in betting and fantasy. At the heart of this success is its robust data science team, which plays a direct role in building and fine-tuning the algorithms that drive Swish’s products for NBA games, player performance, betting odds, and more.

The company’s mission is simple yet ambitious: transform traditional oddsmaking and sports forecasting into a data-first, algorithmic process. Rather than relying on gut instinct or historical biases, Swish operates on a model-driven approach rooted in mathematics, probability, and advanced computing.

This is where the Senior Basketball Data Scientist comes in — a role that has real ownership of the models behind Swish’s flagship basketball analytics.

Key Responsibilities: What You’ll Work On

The Senior Basketball Data Scientist will contribute across the full model development lifecycle. From brainstorming new approaches to deploying production-ready machine learning solutions, the role requires both technical rigor and creative problem-solving.

Here’s a breakdown of key responsibilities:

• Build and Enhance Predictive Systems: Take charge of designing and refining advanced predictive models that drive the core functionality of Swish Analytics’ basketball betting technology.

• Basketball-Specific Feature Development: Apply deep understanding of the game to design tailored feature sets that improve predictive accuracy and algorithm effectiveness.

• Model Lifecycle Management: Take ownership of model pipelines—from proof-of-concept and prototyping to final deployment.

• Performance Analysis: Use both offline and live testing environments to measure model efficiency, tweak weak spots, and increase forecasting precision.

• Software Best Practices: Write clean, reusable code in line with software engineering standards. Commit regularly to shared Git repositories and use CI/CD processes.

• Stakeholder Communication: Document results, methodologies, and insights clearly, communicating them to both technical team members and non-technical stakeholders.

This role will directly impact the quality and credibility of Swish’s predictions — from win probabilities and player projections to dynamic in-game odds.

Who Should Apply: Required Qualifications and Skills

This position is designed for seasoned professionals who bring not only technical skill but also a deep understanding of the basketball ecosystem. Whether you’ve worked in a fantasy sports platform, a betting startup, or a sports data lab, Swish is looking for candidates who can build impactful models at scale.

Minimum Requirements:

• Education: A bachelor’s degree in Data Science, Computer Science, Mathematics, or a related technical field is required. Candidates with a master’s degree will be given additional consideration during the selection process.

• Experience: At least four years of hands-on experience creating and implementing machine learning or statistical models within the sports analytics or betting technology space.

• Basketball Modeling Background: Hands-on experience in creating NBA-focused predictive models is crucial.

• Technical Expertise: Proficiency in:

  • Python

  • SQL (Relational Databases)

  • Machine Learning (supervised, unsupervised)

  • Bayesian Statistics

  • Markov Chain Monte Carlo (MCMC)

  • Probabilistic modeling

• Software & Tools: Familiarity with:

  • Git/GitHub

  • AWS and cloud-based model hosting environments

  • CI/CD pipelines

• Communication Skills: Should possess the ability to clearly convey complex analytical concepts and model outputs to both technical teams and non-technical stakeholders.

Applicants who demonstrate strong leadership, take initiative, and work well in cross-functional teams are likely to be prioritized.

Why Swish Analytics?

From its early days focused on rethinking sports data, Swish Analytics has evolved into a key force behind advanced prediction tools in the betting and fantasy sports space. The company’s tools are already used widely in daily fantasy sports, sportsbooks, and B2B sports platforms, making them a central player in the sports prediction landscape.

At Swish, the focus is on ensuring that every prediction is backed by real data — not guesswork or gut instinct. With a focus on real-time applications, statistical rigor, and innovation, the company’s models help bettors and fans make smarter decisions. Swish is especially well-known in the NBA community for offering accurate game-level and player-level predictions before, during, and after matches.

Employees at Swish enjoy the following advantages:

• Remote-First Environment: Employees can perform their roles from any location within the U.S., offering maximum flexibility and work-life balance

• Salary Range: Annual compensation between $120,000 and $175,000, determined by experience level and qualifications.

• Impactful Work: Direct influence on product-level decisions

• Cross-Functional Teams: Collaborate with data engineers, sports strategists, and product designers

• Growth Opportunities: Learn from industry leaders in betting tech and machine learning

This is not just another data science role — it’s a core contributor position at a tech company where modeling drives the business.

A Commitment to Diversity, Equity, and Inclusion

Swish Analytics is an Equal Opportunity Employer. The company embraces diversity and does not discriminate against any employee or applicant based on race, religion, gender, sexual orientation, national origin, age, disability, or any other protected status. All qualified applicants are encouraged to apply.

Candidates may be required to undergo background and reference checks as part of the hiring process, in accordance with company policy.

Application Process and How to Apply

Interested in joining the Swish team? Candidates can apply directly through the official Swish Analytics career portal or explore opportunities via the company’s social media presence, including their official X account @SwishTalentTeam.

Make sure to submit the following:

• Updated Resume

• Cover Letter (recommended)

• Links to any relevant GitHub/portfolio work

• References (if available)

Swish Analytics may begin interviews as qualified applicants apply, so submitting your application early is recommended.

Final Thoughts

For professionals with a passion for both basketball and data science, this role at Swish Analytics is a golden opportunity. With its strong position in the predictive analytics market and an unwavering focus on technical innovation, Swish offers a meaningful career path for those who want to be at the forefront of sports tech.

Whether you’re currently in a sports data role or transitioning from a more traditional data science field, this position offers everything from competitive pay and remote flexibility to technical ownership and growth. Most importantly, you’ll help shape how fans and bettors experience basketball through cutting-edge algorithms and data products.

👉 Interested candidates can learn more and apply through the official Swish Analytics Careers portal.

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