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Sports Analytics Machine Learning Jobs in Bolingbrook, IL

Cboe Global Markets

Senior Quantitative Data Analyst

Chicago, IL

$88K - $111K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Partner with engineering teams on data ingestion, normalization, and delivery workflows. 3. Advanced Data Analytics & Machine Learning * Apply statistical and machine learning techniques to identify ...

Cboe Global Markets

Senior Quantitative Data Analyst

Chicago, IL · On-site

$88K - $111K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Partner with engineering teams on data ingestion, normalization, and delivery workflows. 3. Advanced Data Analytics & Machine Learning * Apply statistical and machine learning techniques to identify ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Compensation The listed annualized base pay range is primarily based on analysis of similar ...

Ferrara

Sr. Manager, Demand Planning Analytics

Chicago, IL · On-site

$114K - $160K/yr

  • Medical

  • PTO

Drive the adoption of advanced analytics, machine learning, demand sensing, and predictive modeling capabilities to strengthen planning decisions. * Establish and monitor key performance indicators ...

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All JobsSports Analytics Machine Learning JobsSports Analytics Machine Learning Jobs in Bolingbrook, IL

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 Bolingbrook, IL?

For Sports Analytics Machine Learning jobs in Bolingbrook, IL, the most frequently searched job titles are:

What job categories do people searching Sports Analytics Machine Learning jobs in Bolingbrook, IL look for?

The top searched job categories for Sports Analytics Machine Learning jobs in Bolingbrook, IL are:

What cities near Bolingbrook, IL are hiring for Sports Analytics Machine Learning jobs?

Cities near Bolingbrook, IL with the most Sports Analytics Machine Learning job openings:

Sports Analytics Machine Learning jobs near you
Infographic showing various Sports Analytics Machine Learning job openings in Bolingbrook, IL as of August 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 100% In-person job distribution.

Postbaccalaureate Appointee - Machine Learning for Viral Glycosylation Prediction

Argonne National Laboratory

Lemont, IL • On-site

Full-time

Posted 8 days ago

Job description

The Computing, Environment, and Life Sciences (CELS) directorate at Argonne National Laboratory is seeking a Post-Bachelor Appointee to contribute to research at the intersection of artificial intelligence, computational biology, and high-performance computing.
  • The successful candidate will join an interdisciplinary team developing machine learning approaches to understand glycosylation patterns across viral proteins, supporting research that advances computational methods for pathogen characterization, vaccine design, and therapeutic discovery.
  • Working under the guidance of experienced computational scientists, the appointee will assist in the development, implementation, validation, and evaluation of machine learning models for predicting glycosylation sites and glycan occupancy in viral proteins.
  • The position offers an opportunity to develop technical expertise in machine learning, computational biology, scalable software development, and scientific computing while gaining experience in a collaborative national laboratory research environment.

In this role, you can expect to:
  • Assist in the development, implementation, and evaluation of machine learning models for predicting glycosylation sites and glycosylation patterns in viral proteins.
  • Support the design and implementation of graph neural network (GNN) models and other deep learning approaches for learning sequence- and structure-based representations of viral proteins.
  • Collect, curate, preprocess, and integrate biological sequence, structural, and experimental datasets used for model development and benchmarking.
  • Develop software tools and computational workflows using modern machine learning frameworks such as PyTorch, PyTorch Geometric, TensorFlow, or related libraries.
  • Conduct model training, validation, benchmarking, and performance analysis using appropriate statistical and computational evaluation methods.
  • Assist in deploying and optimizing machine learning workflows on Argonne's high-performance computing systems.
  • Document software, datasets, computational workflows, and experimental results to promote reproducibility and maintainability.
  • Collaborate with computational scientists, biologists, and software engineers to interpret model predictions and improve computational methods.
  • Prepare technical reports, presentations, and documentation summarizing research progress and computational results.
  • Contribute to manuscripts, conference presentations, software releases, and other research dissemination activities as appropriate.
  • Participate in project meetings, technical discussions, and collaborative research activities across multidisciplinary teams.
  • Perform additional research and technical duties assigned by the supervisor in support of project objectives.

Expected Outcomes:
  • Success in this position will be demonstrated through:
  • Development of reproducible computational workflows supporting machine learning research on viral glycosylation.
  • Successful implementation and evaluation of machine learning models under the guidance of project scientists.
  • Contribution to scalable software and computational tools supporting ongoing research activities.
  • Effective collaboration within multidisciplinary teams.
  • Preparation of high-quality technical documentation, reports, and research presentations.
  • Growth in technical and research capabilities that prepare the appointee for graduate study or advanced research positions.

Position Requirements
Required Qualifications:
  • Recently completed Bachelor's degree in Computer Science, Bioinformatics, Computational Biology, Data Science, Biomedical Engineering, Applied Mathematics, or a related STEM discipline.
  • Experience programming in Python or a similar scientific programming language.
  • Basic knowledge of machine learning or deep learning methods.
  • Familiarity with one or more machine learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Experience analyzing scientific or biological datasets through coursework, research projects, or internships.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills.
  • Demonstrated ability to work effectively both independently and as part of an interdisciplinary research team.
  • Ability to model Argonne's core values of impact, safety, respect, teamwork, ang integrity.

Preferred Qualifications:
  • Undergraduate research experience in machine learning, computational biology, bioinformatics, or related fields.
  • Experience with graph neural networks or representation learning.
  • Familiarity with protein sequence analysis, structural biology, glycobiology, or bioinformatics.
  • Experience using Linux environments, Git, and software development best practices.
  • Exposure to GPU computing, high-performance computing, or cloud computing environments.
  • Experience presenting research findings or contributing to scientific publications or open-source software projects.

Job Family
Temporary
Job Profile
Postbaccalaureate Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
The expected hiring range for this position is $58,656.00-$92,273.00.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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