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Remote Football Data Science Jobs in Florida (NOW HIRING)

Data Scientist

Tampa, FL · On-site +1

$110K - $130K/yr

Proven ability to translate complex data science findings into clear, actionable insights for non-technical stakeholders * Strong self-direction and communication skills suited for a remote work ...

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Data Scientist

Miami, FL · On-site +1

Master's degree in data science, computer science, marine biology, or related field, OR Bachelor ... Remote * Must be willing to relocate if needed. Contact: If you would like to apply for this ...

Carry out job functions within small, project oriented, multidisciplinary teams of Data Science ... Remote working or telecommuting permitted in all U.S. States, in accordance with company policy.

Performs statistical analysis to build Artificial Intelligence tools that automate certain processes within the unit and implement data science algorithms (e.g. regression, classification and ...

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Remote Football Data Science information

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

AspectRemote Football Data ScienceRemote Sports Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; knowledge of football analyticsDegree in Sports Management, Data Analysis, or related; familiarity with sports data
Work EnvironmentRemote, often collaborative with football teams or analytics firmsRemote or on-site, working with sports organizations or media outlets
Industry UsagePrimarily in football clubs, analytics companies, or sports tech startupsMedia, broadcasting, or sports organizations analyzing various sports

Remote Football Data Science focuses specifically on football analytics, requiring specialized knowledge of football metrics and data science skills. In contrast, Remote Sports Data Analysts work across multiple sports, analyzing diverse datasets. Both roles often work remotely and require similar analytical credentials, but their industry focus and specific expertise differ.

What is a Remote Football Data Scientist?

A Remote Football Data Scientist is a professional who analyzes football (soccer or American football) data to provide insights that help teams, organizations, or media make informed decisions. They use statistical analysis, machine learning, and data visualization techniques to evaluate player performance, predict outcomes, and optimize strategies—all while working remotely. These professionals often collaborate with coaches, scouts, analysts, and other stakeholders by sharing their findings through reports and digital platforms. The role requires strong skills in programming, mathematics, and domain knowledge of football. Working remotely allows them to contribute from anywhere, often using cloud-based tools and virtual collaboration platforms.

What are the typical challenges faced by remote football data scientists, and how can they effectively collaborate with coaching and analytics teams?

Remote football data scientists often face challenges in accessing real-time data, maintaining clear communication across different time zones, and ensuring their analyses align with the needs of coaches and analysts. To overcome these hurdles, it's important to establish regular virtual meetings, use collaborative tools like shared dashboards, and maintain clear documentation of methodologies and findings. Building strong relationships with on-site team members and staying proactive in communication can significantly enhance collaboration and ensure that data-driven insights effectively support team strategies.

What are the key skills and qualifications needed to thrive as a Remote Football Data Scientist, and why are they important?

To thrive as a Remote Football Data Scientist, you need a solid background in statistics, data analysis, and programming (often in Python or R), typically supported by a relevant degree in data science, mathematics, or a related field. Familiarity with sports analytics platforms, machine learning frameworks, and database systems like SQL is commonly required, as are certifications in data analysis or analytics. Strong problem-solving abilities, effective communication, and the capacity to collaborate virtually are vital soft skills for success in this remote, data-driven environment. These skills and qualities enable accurate insights, informed decision-making, and seamless teamwork, ultimately driving competitive advantage for football organizations.
What are the most commonly searched types of Football Data Science jobs in Florida? The most popular types of Football Data Science jobs in Florida are:
What job categories do people searching Remote Football Data Science jobs in Florida look for? The top searched job categories for Remote Football Data Science jobs in Florida are:
What cities in Florida are hiring for Remote Football Data Science jobs? Cities in Florida with the most Remote Football Data Science job openings:
Data Scientist

Data Scientist

ABC Legal Services

Tampa, FL • On-site, Remote

$110K - $130K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

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


Job description

About ABC Legal Services

ABC Legal Services is the nation's premier process serving and court filing company, operating across all 50 states. We are a technology-forward legal services company on a mission to make legal processes faster, smarter, and more reliable. Our data and engineering teams are central to that mission — building models and systems that power operations at scale. We're now looking for a Data Scientist with strong ML engineering and MLOps experience to help us take our machine learning capabilities to the next level.

Role Overview

We're seeking a Data Scientist with hands-on experience in machine learning engineering and MLOps. In this role, you'll own the full model lifecycle — from research and experimentation through deployment, monitoring, and iteration. You'll work within our AWS SageMaker Studio environment and collaborate closely with engineering, operations, and product teams to deliver models that drive measurable business outcomes.

Key Responsibilities

  • Develop, train, and evaluate machine learning models to solve business problems across operations, legal services, and marketing
  • Own the full ML lifecycle: data preparation, feature engineering, model training, validation, deployment, and monitoring
  • Build and maintain MLOps pipelines using AWS SageMaker Studio, including experiment tracking, model registry, and automated retraining workflows
  • Partner with product and operations teams to translate business requirements into data science solutions
  • Monitor deployed models in production, identify performance degradation, and drive continuous improvement
  • Document methodologies, model performance benchmarks, and technical decisions for internal knowledge sharing
  • Stay current with advances in ML and data science tooling, and advocate for best practices across the team

Requirements

Required

  • 3+ years of experience in data science or a closely related role, with demonstrated ML engineering and MLOps responsibilities
  • Strong proficiency in Python for data science and ML development (pandas, scikit-learn, PyTorch or TensorFlow)
  • Hands-on experience with AWS SageMaker Studio for model development, training, and deployment
  • Solid understanding of MLOps principles: model versioning, pipeline automation, drift detection, and production monitoring
  • Experience with SQL and working with structured data in cloud data warehouses or relational databases
  • Proven ability to translate complex data science findings into clear, actionable insights for non-technical stakeholders
  • Strong self-direction and communication skills suited for a remote work environment

Nice to Have

  • Experience in the legal, collections, or financial services industry
  • Background in targeted mail marketing, direct mail modeling, or customer segmentation
  • Familiarity with AI coding agents and agentic development workflows (e.g., Claude, Copilot, Cursor, or similar tools)
  • Experience with propensity modeling, uplift modeling, or response prediction
  • Exposure to LLM-based workflows or applied NLP in a production setting
  • Data engineering experience with modern tooling such as Dagster, Airbyte, and dbt
  • Familiarity with AWS data services including Glue, Lambda, Redshift, and Step Functions

Compensation & Benefits

  • Fully remote position with flexible working hours
  • Comprehensive health, dental, and vision insurance
  • 401(k) with company match
  • Paid time off and company holidays
  • Opportunity to shape data science strategy at a growing, industry-leading company

Salary Range: $110,000-$130,000 depending on experience