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Remote Data Science Sports Jobs in Kansas (NOW HIRING)

$108K - $143K/yr

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent ... Flexible Work Environment Whether remote, hybrid, or in-office, we support work arrangements that ...

$108K - $143K/yr

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent ... Flexible Work Environment Whether remote, hybrid, or in-office, we support work arrangements that ...

Intermediate knowledge of HPC / Data Science * Water Resources Engineering Modeling Software ... Experience with data processing imagery and LiDAR from web services, UAS, or other remote sensing ...

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... Bachelor's degree in Geographic Information Systems, Computer Science, Geography, or a related ...

Configure and manage map services and data publishing workflows to ensure timely and accurate data ... Bachelor's degree in Geographic Information Systems, Computer Science, Geography, or a related ...

$61K - $79K/yr

StackAdapt is a remote-first company; we are open to candidates located anywhere in Canada and the ... Partner closely with Engineering Managers, Product Managers, Designers, ML/Data Science, and other ...

StackAdapt is a Remote First company, we are open to candidates located anywhere in North America ... A strong understanding of computer science fundamentals: data structures, system design, cloud ...

This Counsel will work closely with product managers, engineers, data science, compliance, privacy ... StackAdapt is a remote first company. This role is open to applicants currently located in Canada ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

Showing results 41-60

Remote Data Science Sports information

What are the key skills and qualifications needed to thrive as a remote data science sports professional?

To thrive as a Remote Data Science Sports professional, you need a strong background in statistics, data analysis, and sports knowledge, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with programming languages such as Python or R, proficiency in data visualization tools, and experience with machine learning frameworks are typically required. Excellent problem-solving abilities, communication skills, and self-motivation are crucial soft skills for collaborating remotely and translating complex data into actionable insights. These skills ensure accurate sports data modeling, effective remote teamwork, and valuable contributions to decision-making in sports organizations.

What is the difference between Remote Data Science Sports vs Remote Data Analysis Sports?

AspectRemote Data Science SportsRemote Data Analysis Sports
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves modeling and machine learningData interpretation, reporting, and visualization, often in business contexts
Employer & Industry UsageTech companies, sports analytics firms, media outletsSports teams, media companies, sports analytics agencies

Remote Data Science Sports involves advanced modeling, machine learning, and statistical analysis, requiring higher technical credentials. Remote Data Analysis Sports focuses on interpreting data, creating reports, and visualizations. Both roles are common in sports industry analytics but differ in complexity and technical depth.

How do remote data science professionals in the sports industry typically collaborate with coaches and analysts to turn data insights into actionable strategies?

Remote data science professionals in the sports industry often work closely with coaches, analysts, and other stakeholders through regular virtual meetings and collaborative platforms. They translate complex data findings into intuitive visualizations and reports, making it easier for non-technical team members to understand and apply insights. Communication and responsiveness are key, as data scientists may need to quickly adjust analyses based on feedback or new priorities from the sports staff. Building strong relationships and maintaining clear channels of communication help ensure that data-driven recommendations are effectively integrated into training, game strategies, and player development.

What is a remote data science sports job?

A remote data science sports job involves analyzing sports-related data to extract insights, build predictive models, and support decision-making, all while working from a location outside of a traditional office, typically from home. Professionals in this role use statistical methods, programming, and machine learning to evaluate player performance, game strategies, or fan engagement. Their work helps sports teams, leagues, media companies, and betting firms make evidence-based decisions. Remote positions offer flexibility and often require strong communication skills to collaborate with teams virtually. The demand for these roles is growing as the sports industry increasingly relies on data-driven strategies.
What cities in Kansas are hiring for Remote Data Science Sports jobs? Cities in Kansas with the most Remote Data Science Sports job openings:

Senior Product Manager (AI division)

Locatee Ag

On-site, Remote

$108K - $143K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 22 days ago


Job description

Let's Tango. Where Innovation Meets Impact. At Tango Analytics, we're all about helping businesses make smarter decisions through powerful technology, insightful data, and a whole lot of collaboration.

Whether you're a creative thinker, a strategic planner, a tech wizard, or a customer champion, there's a place for you on our team. We believe work should be meaningful and fun - so if you're ready to make a difference while enjoying the journey, come join us and let's Tango. We are looking for a Senior Product Manager (AI division) to join our dynamic and growing Product team.

Key Responsibilities: Own AI product areas within Tango's intelligence layer: define what to build, write acceptance criteria including accuracy thresholds and human-in-the-loop requirements, and ship features with the AI Engineering team. Partner with AI Engineering as a peer. Earn credibility through product judgment and evaluation standards.

Your evaluation framework ships before the feature does. Design trust surfaces for enterprise customers: confidence disclosure, citation standards, audit trails, and explainability are product decisions you own. Run discovery with enterprise customers through design partner conversations, usage data analysis, and competitive landscape tracking.

Your discovery changes what gets built. Frame AI investment in customer outcome terms: retention impact, expansion signal, time-to-value. Be clear about what's not on the roadmap and defend the decision.

Define enterprise-grade AI guardrails: confidence thresholds, latency requirements, and human-in-the-loop triggers appropriate for customers with compliance obligations. Continuously evolve organizational and engineering practices to support and grow the Tango intelligence layer. About You: 5+ years in product management with shipped and validated AI or ML features in a B2B SaaS environment.

Proven ability to partner with AI Engineering as a peer; earns technical credibility through product judgment; understands model behavior well enough to write meaningful acceptance criteria and constraints. Track record of defining "ready to ship" before Engineering starts building. Evaluation criteria, guardrail requirements, and trust surface design are PM-owned decisions.

Comfortable operating within a team where a director sets the platform strategy while you own full product area decisions and execution. Fluent in LLM-specific product patterns: RAG, evaluation frameworks, prompt versioning, latency/cost trade-offs, and human-in-the-loop design. Keeps abreast of current best practices and developments.

Uses AI tools actively in daily workflow as demonstrated practice, not theoretical interest. Experience designing enterprise trust surfaces: confidence disclosure, citation standards, explainability, and audit trails for users with compliance obligations. Can translate dense technical concepts such as model behavior, evaluation methodology, and infrastructure constraints into clear product decisions and crisp stakeholder communication.

Enterprise SaaS experience with complex data workflows, platform infrastructure, or multi-tenant environments strongly preferred. Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience. What We Offer We're committed to creating an environment where you can thrive-professionally and personally.

Our offerings include: Competitive Compensation We recognize and reward your contributions with a salary package that reflects your value. Comprehensive Benefits Including health, dental, and vision insurance, a 401(k) plan with company match, and generous paid time off to support your well-being. Flexible Work Environment Whether remote, hybrid, or in-office, we support work arrangements that promote productivity and balance.

Inclusive & Collaborative Culture We foster a workplace where diverse perspectives are valued, teamwork is encouraged, and everyone has a voice. Tango is proud to be an equal opportunity employer. We are committed to equal opportunity regardless of race, ethnicity, religion, parental status, sexual orientation, age, citizenship, disability, or veteran status.