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Sports Analytics Machine Learning Jobs in Minnesota

Lead AI/ML Engineer - Remote

Eden Prairie, MN ยท On-site +1

$104K - $137K/yr

Build machine learning models; perform proof-of-concept experiments; optimize and deploy models to production; partner with software engineers to productionize ML models * Perform hands-on analysis ...

Lead AI/ML Engineer - Remote

Eden Prairie, MN ยท On-site +1

$104K - $137K/yr

Build machine learning models; perform proof-of-concept experiments; optimize and deploy models to production; partner with software engineers to productionize ML models * Perform hands-on analysis ...

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Sports Analytics Machine Learning information

What is sports analytics machine learning?

Sports analytics machine learning is the application of data science and machine learning techniques to analyze sports data, such as player statistics, game outcomes, and biometric information. Professionals in this field develop models to identify patterns, predict player performance, optimize team strategies, and gain competitive advantages. This work involves collecting large datasets, cleaning and processing data, and using algorithms to extract actionable insights that can benefit teams, coaches, and athletes. Sports analytics with machine learning is increasingly used in professional sports to inform decisions about training, recruitment, and game tactics.

How do Sports Analytics Machine Learning professionals typically collaborate with coaches and athletes to impact game strategy?

Sports Analytics Machine Learning professionals often work closely with coaches and athletes by translating complex data insights into practical recommendations. They attend strategy meetings, present findings through visualizations, and help interpret trends that can influence training, player selection, and in-game tactics. Effective communication is key, as these professionals must bridge the gap between technical analyses and real-world sports applications. This collaborative environment not only enhances team performance but also provides opportunities to see the direct impact of your work on the field.

What are the key skills and qualifications needed to thrive as a Sports Analytics Machine Learning Specialist, and why are they important?

To thrive as a Sports Analytics Machine Learning Specialist, you need a strong background in statistics, data analysis, programming (typically in Python or R), and an understanding of machine learning algorithms, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools, sports databases, and machine learning frameworks like TensorFlow or scikit-learn is essential, along with experience using SQL and data pipelines. Strong problem-solving, communication, and collaboration skills help translate complex data findings into actionable insights for coaches, players, and stakeholders. These skills are crucial for extracting meaningful patterns from vast sports datasets and driving performance improvements or strategic decisions within sports organizations.
What are popular job titles related to Sports Analytics Machine Learning jobs in Minnesota? For Sports Analytics Machine Learning jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Sports Analytics Machine Learning jobs? Cities in Minnesota with the most Sports Analytics Machine Learning job openings:
Senior Analyst, Analytics & Insights

Senior Analyst, Analytics & Insights

Bold Orange Company, LLC

Minneapolis, MN โ€ข On-site, Remote

$85K - $125K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 22 days ago


Job description

About Bold Orange:
Bold Orange (BOCO) is a customer experience company. We believe authentic human connections are the single most important driver of business and societal progress. We exist to create these connections across the customer lifecycle, from acquisition to engagement to retention. Our culture is one of curiosity, collaboration, proactivity and always bringing the outside, future focused perspective to our clients.
Position Summary:
Bold Orange (BOCO)'s growing Analytics & Insights team is seeking a Senior Analyst with at least 5+ years of hands-on experience analyzing marketing & customer datasets and experience building machine learning models and/or statistical experiments.
A Senior Analyst in the team will be expected to lead the hands-on analytics work end-to-end in these projects, with constant support and mentorship from a Director. This end-to-end work can include identifying what datasets are worth analyzing, provisioning & cleaning data, data exploration & modelling (clustering, forecasting, driver models, etc.), developing actionable insights, designing compelling data visualizations, and presenting / discussing recommendations with clients.
Across BOCO Analytics projects, someone in the Senior Analyst role will need to leverage their previous experience and bring a curious, creative energy for ongoing learning. With analytics work spanning customer transactions data, search/AI & web analytics data, email & SMS engagement data, media investment & engagement data, product & in-store reviews data, and more, our team needs to bring fundamental analytics skills and an agile mentality for exploring new domains.
The ideal candidate has at least 5+ years of hands-on marketing analytics experience including knowledge of both SQL and Python, comfort with Snowflake and/or other cloud data platforms, and demonstrated experience organizing, integrating, analyzing, and interpreting data to form a clear, compelling story.
Experience with digital analytics tools (Google Analytics, digital ads platforms, ESPs, etc.) is not required but preferred.
Responsibilities:
  • Analyze integrated marketing and customer journey datasets to understand the drivers of success/failure in the context of client strategy and develop clear recommendations for a non-technical audience from this data.
  • Build machine learning models (scikit-learn, XGBoost) & run statistical experiments (control vs. exposed, MAB) to validate, predict, and identify drivers of marketing outcomes.
  • Explore and learn to leverage new analytics datasets and tools, helping clients understand how they can support insights and optimization.
  • Design, build, and train clients to understand reporting, dashboards, and performance insights for ongoing client delivery (Data Studio, PowerBI, Tableau, PowerPoint).
  • Present and discuss analysis with internal stakeholders and clients, including adapting content for different audiences.
  • Build and maintain data architecture documentation to ensure clarity across teams on what datasets are canonical and where they come from.
  • Mentor junior analytics team members to support their ongoing development, always promoting creativity as well as structured thinking.

Required Qualifications:
  • At least 5+ years domain experience within digital analytics, marketing analytics or related field.
  • Working knowledge of SQL and Python (incl. Pandas) for analytics and machine learning
  • Experience with statistical modeling and experimental design, including randomized control designs, regression modeling, decision tree / random forest classification, or other machine learning approaches.
  • Bachelor's degree in data science, business analytics, social sciences, or another related discipline with meaningful exposure to data analysis.
  • Ability to thrive in a highly collaborative, cross-functional environment where analytics supports and works closely with tech, creative, and execution teams
  • Innately curious and keen to learn new skills and new tools
  • Excellent communication skills - verbal and written. This is a client-facing analytics role.

Preferred Qualifications:
  • Experience with machine learning & modeling tools including Scikit-Learn, XGBoost, PyMC, Statsmodels, Prophet, and/or Dataiku
  • Experience with cloud data platforms including Snowflake, Databricks, AWS, Google Cloud, etc. Snowflake experience is especially valuable.
  • Experience with data analysis & visualization tools including Data Studio (formerly Looker Studio), Tableau, Sigma, PowerBI, and/or Datorama.
  • Experience with digital experience analytics tools including Google Analytics, Google Ads, Meta Ads, TikTok Ads, and/or SEMRush.
  • Experience using AI tools (including custom skills / agents) to accelerate data analysis, code generation, or insight development.

$85,000 - $125,000 a year
We benchmark salaries across industry standards and local markets to ensure we offer competitive, fair compensation. Final offers reflect a candidate's skills, experience, and location. The annual base for this position is anticipated to be between $90K to $125k. Final compensation will be dependent on the ideal candidates experience and local market at the time of hire.
Benefits That Matter:
Our benefits are designed to support life's many stages-expected and unexpected. Eligible employees can access:
โ€ข Medical, dental, and vision insurance
โ€ข Virtual mental health support
โ€ข Health Savings and Flexible Spending Accounts (including dependent care)
โ€ข Infertility and critical illness benefits
โ€ข 401(k) with generous 6-10% employer contribution
โ€ข Paid parental leave
โ€ข Tuition reimbursement
โ€ข Free parking and commuter support
Note: Some benefits apply only to full-time employees.
Who We Are:
Our tone is professionally sassy. We embrace meat raffles, hot seats, and the occasional Jell-O shot. We like staff meetings that are informative, educational, and at times, damn funny. We believe in no hierarchy, no bullshit, no politics. Just honest, hard work and great fun.
Equal Opportunity Employer:
We are an equal opportunity employer, dedicated to a policy of nondiscrimination in employment on any basis including race, color, creed, gender, sexual orientation, age, disability, religion, national origin, marital status, familial status, ancestry, status as a veteran, status with regard to public assistance and any other characteristic protected by law. Bold Orange does not and will not discriminate against employees, prospective employees, clients, or vendors.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are made by humans. If you would like more information about how your data is processed, please contact us.