2

Remote Football Data Analyst Jobs in Kentucky (NOW HIRING)

DemandFactor is a data-driven B2B growth and demand-generation company helping brands find, engage ... Manage marketing KPIs, analytics, attribution, and budget * Build and grow the marketing team What ...

Analyst, Accounts Receivable

Louisville, KY ยท On-site +1

$64K - $66K/yr

... data and transactions. You will monitor and reconcile franchisee and customer account activity ... This role is fully remote. Salary Range: $64,900 - $66,000 + bonus eligibility. This is the ...

Pharmacovigilance Expert

Louisville, KY ยท Remote

$70 - $80/hr

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... safety data analysis. * Expertise in reconciling aggregate safety data and identifying ...

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... safety data analysis. * Expertise in reconciling aggregate safety data and identifying ...

Showing results 21-40

Remote Football Data Analyst information

What is a remote football data analyst?

A Remote Football Data Analyst is a professional who analyzes football (soccer) data and statistics to provide insights on team performance, player metrics, and match outcomes, all while working from a remote location. They use various data sources and analytical tools to interpret match data, identify trends, and support coaching staff, scouts, or media organizations. Their work may include creating reports, visualizing data, and building statistical models to inform decisions. This role typically requires strong analytical skills, proficiency in data analysis software, and a deep understanding of the game.

What are the key skills and qualifications needed to thrive as a remote football data analyst?

To thrive as a Remote Football Data Analyst, you need strong analytical skills, a solid understanding of football tactics, and a degree in statistics, mathematics, or a related field. Proficiency with data analysis tools like Python, R, SQL, and specialized sports analytics platforms such as Opta or Wyscout is typically required. Attention to detail, effective communication, and the ability to work independently are essential soft skills for remote collaboration and insight delivery. These skills enable accurate data interpretation, actionable insights, and effective support for coaching or management decisions in a competitive sports environment.

How do remote football data analysts typically collaborate with coaching staff and scouts despite working off-site?

Remote Football Data Analysts regularly use digital communication tools and data visualization platforms to share insights with coaching staff and scouts. Collaboration often involves scheduled video meetings, sharing dashboards, and providing real-time data interpretations to support tactical decisions. While not physically present, analysts are integral to pre- and post-match briefings, and their ability to convey complex data clearly is crucial in helping the team understand and utilize the insights effectively.

What is the difference between Remote Football Data Analyst vs Remote Sports Data Analyst?

AspectRemote Football Data AnalystRemote Sports Data Analyst
Required CredentialsDegree in Sports Analytics, Data Science, or related field; knowledge of football statisticsDegree in Sports Analytics, Data Science, or related field; broad sports knowledge
Work EnvironmentRemote, often with sports teams, analytics firms, or media companiesRemote, employed by sports organizations, media outlets, or analytics agencies
Industry UsageFocused on football-specific data analysis and performance metricsAnalyzes data across multiple sports, including football, basketball, and others
Common Search/ComparisonOften compared for specialization in footballBroader sports analysis roles

The Remote Football Data Analyst specializes in football-specific data, requiring knowledge of football metrics and analytics. In contrast, the Remote Sports Data Analyst covers multiple sports, offering a broader scope. Both roles share similar credentials and work environments but differ in industry focus and specialization.

What job categories do people searching Remote Football Data Analyst jobs in Kentucky look for?

The top searched job categories for Remote Football Data Analyst jobs in Kentucky are:

What cities in Kentucky are hiring for Remote Football Data Analyst jobs?

Cities in Kentucky with the most Remote Football Data Analyst job openings:

Infographic showing various Remote Football Data Analyst job openings in Kentucky as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Digital Chemistry Specialist - Remote

micro1 AI

Lexington, KY โ€ข Remote

$90 - $120/hr

Part-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.