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Remote Entry Level Sports Analytics Jobs (NOW HIRING)

Jobgether

$80K - $110K/yr

Develop, enhance, and maintain production-ready computer vision models for sports video analytics ... Fully remote position for professionals residing in Europe. * Flexible working hours with a strong ...

Only Data Entry

Data Entry Assistant - Entry Level / Remote

$17.25 - $22.75/hr

Data Entry Assistant - Entry Level / Remote Are you ready to embark on a career that offers endless ... ready for analysis. Responsibilities: * Accurately input, update, and maintain large volumes of ...

Only Data Entry

Data Entry Assistant - Entry Level / Remote

$17.25 - $22.75/hr

Data Entry Assistant - Entry Level / Remote Are you ready to embark on a career that offers endless ... analysis. Responsibilities * Accurately input, update, and maintain large volumes of data into our ...

Only Data Entry

Data Entry Assistant - Entry Level / Remote

$17.25 - $22.75/hr

Data Entry Assistant - Entry Level / Remote Are you ready to embark on a career that offers endless ... ready for analysis. Responsibilities: * Accurately input, update, and maintain large volumes of ...

Only Data Entry

Data Entry Assistant - Entry Level / Remote

$17.25 - $22.75/hr

Data Entry Assistant - Entry Level / Remote Are you ready to embark on a career that offers endless ... ready for analysis. Responsibilities: * Accurately input, update, and maintain large volumes of ...

Link Up Overseas

Remote Data Entry Assistant / Entry Level

$17.25 - $22.75/hr

About the job Remote Data Entry Assistant / Entry Level Are you ready to kickstart your career in ... Basic analytical and problem-solving skills. * Adaptability and a willingness to learn new tools ...

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Remote Entry Level Sports Analytics information

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How much do remote entry level sports analytics jobs pay per month?

As of Jul 14, 2026, the average monthly pay for remote entry level sports analytics in the United States is $6,290.58, according to ZipRecruiter salary data. Most workers in this role earn between $5,708.33 and $6,708.33 per month, depending on experience, location, and employer.

Is there a demand for sports analysts?

The demand for sports analysts is growing as teams and organizations increasingly rely on data-driven insights to improve performance and strategy. Entry-level sports analytics roles are available in professional leagues, college programs, and media companies, often requiring skills in statistical software, data visualization, and sports knowledge. The field is expected to expand with the increasing use of advanced analytics and technology in sports.

Will sports analytics be taken over by AI?

Sports analytics roles, including entry-level positions, involve interpreting data to support team strategies and player performance. AI tools can automate data collection and analysis, but human expertise is essential for contextual understanding and decision-making, making these roles unlikely to be fully replaced by AI soon.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, including in sports analytics roles. Success depends on acquiring relevant skills such as data visualization, statistical analysis, and proficiency with tools like Excel, SQL, or Python, which can be learned at any age through online courses or certifications.

How to become a sports analyst with no experience?

To become a remote entry-level sports analyst with no experience, focus on developing skills in data analysis, statistics, and sports knowledge through online courses and self-study. Gaining proficiency in tools like Excel, SQL, or sports analytics software, and building a portfolio of projects or insights can help demonstrate your abilities to employers.
More about Remote Entry Level Sports Analytics jobs
What cities are hiring for Remote Entry Level Sports Analytics jobs? Cities with the most Remote Entry Level Sports Analytics job openings:
What states have the most Remote Entry Level Sports Analytics jobs? States with the most job openings for Remote Entry Level Sports Analytics jobs include:
What job categories do people searching Remote Entry Level Sports Analytics jobs look for? The top searched job categories for Remote Entry Level Sports Analytics jobs are:
Remote Entry Level Sports Analytics jobs near you
Infographic showing various Remote Entry Level Sports Analytics job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 1% Internship, 92% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $75,487 per year, or $36.3 per hour.

Senior Applied Computer Vision Engineer

Jobgether

Remote

$80K - $110K/yr

Full-time

PTO

This job post has expired today. Applications are no longer accepted.

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Applied Computer Vision Engineer based in Netherlands.

Join a highly technical engineering team focused on transforming sports video into actionable insights through advanced computer vision and machine learning. In this role, you will develop, optimize, and scale production-grade vision systems capable of handling complex real-world video environments. You'll work across the full lifecycle of computer vision solutions, from experimentation and model development to deployment and continuous improvement. This position offers the opportunity to solve challenging problems involving object detection, tracking, camera calibration, and video analytics while collaborating with cross-functional engineering teams. The environment is remote-first, flexible, and driven by innovation, giving you the autonomy to lead technical initiatives with meaningful impact.

Accountabilities
  • Develop, enhance, and maintain production-ready computer vision models for sports video analytics, including player and ball detection, tracking, event recognition, and identity association.
  • Design and improve geometric computer vision solutions such as camera calibration, homography estimation, field registration, and coordinate mapping.
  • Evaluate existing computer vision pipelines, identify performance bottlenecks, analyze failure modes, and implement practical improvements to increase accuracy, scalability, and robustness.
  • Adapt machine learning models and vision pipelines to support new sports, leagues, stadiums, camera configurations, and varying video quality conditions.
  • Design and execute experiments covering dataset creation, augmentation, model training, fine-tuning, evaluation, and production readiness.
  • Collaborate with data, software, platform, and DevOps teams to deploy scalable machine learning solutions into production environments while improving inference performance, monitoring, and operational reliability.
  • Define evaluation metrics, testing strategies, and quality assurance processes to ensure consistent model performance over time.
  • Lead technical initiatives from early research and prototyping through deployment, communicating technical decisions and trade-offs effectively across engineering and stakeholder teams.
Requirements
  • Extensive experience building, deploying, and improving production-grade computer vision systems.
  • Strong proficiency in Python and modern deep learning frameworks such as PyTorch.
  • Hands-on expertise in video-based computer vision, including object detection, multi-object tracking, event recognition, identity association, or video analytics.
  • Solid understanding of geometric computer vision concepts including camera calibration, homography estimation, projective geometry, and mapping image coordinates to real-world environments.
  • Experience improving tracking systems in challenging scenarios involving occlusions, noisy detections, identity preservation, and object interactions.
  • Demonstrated ability to evaluate model performance, identify weaknesses, and implement effective optimization strategies.
  • Experience adapting models to diverse real-world environments using techniques such as transfer learning, domain adaptation, data augmentation, and fine-tuning.
  • Strong software engineering practices with the ability to write clean, maintainable, production-quality code.
  • Ability to work independently, prioritize multiple initiatives, and drive projects through completion.
  • Excellent communication and collaboration skills within cross-functional and client-facing environments.
  • Experience in sports analytics, broadcast video, multi-camera systems, GPU-accelerated video processing, OCR, MLOps, backend systems, cloud infrastructure, or technical leadership is considered an advantage.
Benefits
  • Competitive salary based on experience.
  • Comprehensive benefits package including paid vacation and sick leave.
  • Fully remote position for professionals residing in Europe.
  • Flexible working hours with a strong focus on work-life balance.
  • Home office equipment allowance and the option to use a coworking space when preferred.
  • No business travel required.
  • Opportunity to work alongside highly experienced international engineering professionals.
  • Collaborative, fast-paced environment with excellent opportunities for technical growth and career development.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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