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Sports Analytics Machine Learning Jobs in Inverness, FL

Identifies and implements machine or equipment improvements, including the design, creation, and ... Lead HAZOP analysis for process changes and new equipment introductions * Conversion and rollout ...

Identifies and implements machine or equipment improvements, including the design, creation, and ... Lead HAZOP analysis for process changes and new equipment introductions * Conversion and rollout ...

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 job categories do people searching Sports Analytics Machine Learning jobs in Inverness, FL look for? The top searched job categories for Sports Analytics Machine Learning jobs in Inverness, FL are:
What cities near Inverness, FL are hiring for Sports Analytics Machine Learning jobs? Cities near Inverness, FL with the most Sports Analytics Machine Learning job openings:
Lead Data Scientist (Artificial Intelligence/Machine Learning)

Lead Data Scientist (Artificial Intelligence/Machine Learning)

US Department of the Treasury

Ocala, FL • On-site

$125K/yr

Other

Posted 8 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

229th of 675 rated public administrative organizations


Job description

WHAT IS INFORMATION TECHNOLOGY ?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s):
    • IT - Taxpayer Services and Online Accounts
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes:

  • Designing, developing, integrating, testing, and supporting conversational AI solutions, virtual assistants, chatbots, digital messaging platforms, voice automation, interactive voice response (IVR) platforms, or generative AI-enabled customer engagement solutions in a production environment.
  • Developing and optimizing natural language understanding (NLU), natural language processing (NLP), speech recognition, intent classification, entity recognition, conversational workflows, or automated self-service solutions supporting customer interactions across voice and digital channels.
  • Designing, testing, implementing, and refining prompt engineering strategies, generative AI workflows, large language model (LLM) integrations, and AI-assisted customer engagement capabilities to improve automation, containment, customer experience, and operational outcomes.
  • Integrating conversational AI, generative AI, voice, chat, messaging, or digital engagement platforms with enterprise applications, APIs, backend systems, authentication services, customer data platforms, or knowledge management solutions.
  • Demonstrating subject matter expert (SME)-level proficiency in at least one modern programming language such as Java or Python, including development of backend services, automation, integrations, data processing pipelines, or conversational application logic.
  • Analyzing customer interaction data, conversation transcripts, chat sessions, operational metrics, and user behavior to identify trends, improve AI performance, evaluate model effectiveness, and enhance customer experience outcomes.
  • Developing, querying, and analyzing large datasets using cloud-based analytics platforms and data warehouses to support AI model evaluation, operational reporting, and business decision-making.
  • Troubleshooting and resolving complex system integration, application reliability, authentication, speech processing, conversational AI, generative AI, digital engagement, or performance issues across interconnected platforms.
  • Applying DevSecOps, CI/CD pipelines, automated testing, version control, and agile software development practices in enterprise environments.
  • Collaborating with business stakeholders, architects, engineers, cybersecurity personnel, data scientists, and operations teams to translate business requirements into AI-enabled technical solutions.

AND
You must also meet the following requirement(s):

  • PERFORMANCE RATING: Current federal employees must have at least a fully successful or equivalent performance rating to receive consideration.
  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): Federal employees must meet time-in-grade requirements. For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03, or 04 positions.


For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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