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Remote Data Science Sports Jobs in Texas (NOW HIRING)

Work Environment: * 100% remote - must work in CST * 8am-5pm (9 hour day with one hour lunch break ... Data science experience * Retail experience * SQL Coding, Microsoft Access, Macro building ...

Job Title Senior Data Science Consultant, Insurance - Remote Requisition Number R7828 Senior Data Science Consultant, Insurance - Remote (Open) Location Arizona - Home Teleworkers Additional ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

Lead Data Scientist

Frisco, TX · On-site +1

$138K - $272K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Data Scientist

Dallas, TX · On-site +1

Data Science is a driver of significant competitive advantage for Kemper and is critical to the ... Remote options are available for non-local candidate. * The range for this position is $93,300 to ...

Data Scientist

Frisco, TX · On-site +1

$104K - $180K/yr

Job Summary The Senior Associate Data Science role at Bread Financial delivers best-in-class ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Data Scientist I/II (Remote - US)

TX · On-site +1

$93K - $175K/yr

Remote US Anticipated Start Date: 08/03/2026 The US base salary range for this full-time position ... Apply data science skills to analyze large, complex datasets and identify meaningful patterns that ...

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Remote Data Science Sports information

What are the key skills and qualifications needed to thrive as a Remote Data Science Sports professional, and why are they important?

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.

Do data scientists work in sports?

Data scientists in sports analyze large datasets to improve team performance, player health, and game strategies. They use tools like Python, R, and machine learning techniques to extract insights from sports data, often working for teams, leagues, or sports analytics companies.

How much do sports data scientists make?

Sports data scientists typically earn between $70,000 and $120,000 annually, depending on experience, location, and the level of the organization. Entry-level roles may start lower, while experienced professionals or those working with major sports teams or organizations can earn higher salaries, especially with advanced skills in statistical analysis, machine learning, and programming tools like Python or R.

How much do NFL data scientists make?

NFL data scientists typically earn between $70,000 and $130,000 annually, depending on experience, education, and the complexity of projects. They often work with statistical software, machine learning tools, and sports analytics platforms in a collaborative environment.

Can data science jobs be done remotely?

Remote data science jobs, including roles in sports analytics, are common and often involve tasks such as data analysis, modeling, and visualization using tools like Python or R. Many companies offer remote positions to access a wider talent pool, and these roles typically require strong communication skills and familiarity with cloud-based collaboration platforms.

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 are the most commonly searched types of Data Science Sports jobs in Texas? The most popular types of Data Science Sports jobs in Texas are:
What job categories do people searching Remote Data Science Sports jobs in Texas look for? The top searched job categories for Remote Data Science Sports jobs in Texas are:
What cities in Texas are hiring for Remote Data Science Sports jobs? Cities in Texas with the most Remote Data Science Sports job openings:
Infographic showing various Remote Data Science Sports job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Remote Data Analyst

Jobsultant Solutions

Dallas, TX • Remote

Contractor

Re-posted 16 days ago


Job description

The Nations 2nd largest Technical Staffing and Services Firm, has an opening for a Remote Analyst at a global leader in retail pharmacy for a 6-month contract with the opportunity for extension or conversion.

Summary:

The Walgreens Merchandise Planning Analytics team manages reporting, analysis, and tool building for the Walgreens Merchandising team. They support a team of 100+ merchants and 40+ planners to optimize performance of the Walgreens Front End (non-Pharmacy) businesses.

Work Environment:

  • 100% remote - must work in CST
  • 8am-5pm (9 hour day with one hour lunch break 12pm-1pm).
    • The hours can be flexible per above but minimally need 30 hours a week in order to fulfill the business needs

Responsibilities:

  • Own Brand (private label) reporting, recapping, tracking, and analysis, including ad-hoc analysis based on business needs
  • Item level historical analysis and recapping
  • Item level future looking forecast
  • Scope will be thousands of Own Brand items (at item level)
  • System/ tool used is Excel
  • Project will involve complex excel formulas and ability to synthesize large data sets into meaningful executive recaps

Top Must-Have Skills:

  • Bachelors Degree and at least 3-5 year of experience in one or more of the following: analytics, data science, finance, financial analysis, assortment planning, retail, procurement/purchasing, merchandising
  • Minimum 3 years experience in data analytics or other related field with strong understanding of retail merchandising basics (i.e. category management) and merchandising organization structures and processes
  • Outstanding analytical and problem-solving skills partnered with storytelling finesse
  • Ability to conduct complex quantitative analysis and build analytical models using Microsoft Excel
  • Ability to communicate effectively and succinctly both verbally and in writing via Microsoft PowerPoint
  • Ability to manage and prioritize multiple assignments and meet tight deadlines
  • Ability to develop effective working relationships with Merchandising, Planning, Finance and other stakeholders
  • Ability to work independently and adapt to changing work priorities
  • Retail math background; skills such as item level forecasting based on demand patterns or sell through/ sales/ profit goals, knowledge of sales by type and AUR impacts, all inventory and sales metrics
  • Intermediate/Advanced level skill in Microsoft Excel (for example: using SUM/SUMIFS, Subtotals, VLOOKUP, HLOOKUP, Macros, Pivot tables) - CRITICAL SKILL NEEDED FOR ROLE, most work will be done in excel
  • Intermediate level skill in Microsoft Word and PowerPoint

Top Nice-to-Have Skills:

  • MBA preferred; Science, Technology, Engineering, Mathematics and/or other quantitative analytical degree a plus
  • Data science experience
  • Retail experience
  • SQL Coding, Microsoft Access, Macro building

Education / Experience Requirements:

  • 3-5 year experience in Analytics or Data Science, Merchandising background