Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Baseball Analyst/Data Scientist

Miami Marlins and loanDepot park
Tipton
2 days ago
Create job alert

At the Miami Marlins, we make waves — on and off the field.

We’re built for sustainable success thanks to our commitment to be great teammates, bold innovators, and thinking long-term. These three pillars guide us in championing a winning culture across the organization. The work we do doesn’t just impact our team — it reaches fans and communities across South Florida.

Position Summary

As a Baseball Analyst in Baseball Solutions or a Data Scientist in Baseball Research, you will be responsible for supporting the department in developing sophisticated statistical models, advancing our ability to forecast player performance, and translating insights into actionable recommendations for the Miami Marlins front office. These roles involve prioritizing and executing research requests, creating innovative models, and collaborating with other departments across baseball operations. Strong statistical modeling skills, technical expertise, ability to communicate to technical and non-technical audiences, and a passion for baseball are essential for success in these positions. Note that these are two separate positions, and applicants will automatically be considered for both positions.

Essential Functions

Construct advanced statistical models to support decision-making within Baseball Operations. Convert key baseball (and physical) concepts into metrics, features, and insights for consumption by the Baseball Solutions and Baseball Research departments, as well as those outside of R&D. Develop and maintain production pipelines for daily implementation of statistical models. Collaborate with other analysts, engineers, and stakeholders to identify opportunities for improvement. Manage and clean large datasets from various sources. Provide actionable insights through detailed statistical analysis. Assist with recruiting and evaluating applicants to join the Baseball R&D team. Create and maintain documentation outlining departmental best practices.

Our Values

We Are Great Teammates

Supports and encourages colleagues.Provides and receives feedback without judgement or ego.Holds one another to a high standard.Provides help and encouragement proactively.Assumes positive intentions from others. Looks for ways to help make their teammates better.

We Are Innovators

Embraces a growth mindset.Challenges conventional wisdom.Unafraid to fail.Pushes boundaries and doesn't accept impossible.Asks why and asks why not.

We Think Long-Term

Asks: what can I do today that will pay off a year from now. Eschews instant gratification for bigger benefits in the future.Always trying to think three steps ahead.

Skill Requirements

Proficiency in programming languages such as Python, R, and SQL.Experience in advanced modeling approaches preferred (Bayesian methods, neural networks, time-series forecasting)Experience with probabilistic programming languages preferred (Stan, PyMC)Strong analytical and problem-solving skills.Excellent written and verbal communication skills.Ability to manage multiple tasks and meet deadlines.Collaborative mindset and willingness to work in a team environment.Willingness to relocate to Miami and commute to loanDepot Park.Familiarity with public baseball research.Experience with Git and cloud-based computing preferred.

Education & Experience Guidelines

Bachelor’s degree in Statistics, Mathematics, Data Science, or a related quantitative field. Graduate degree is preferred, or equivalent real-world experience.0-2 years of experience in a data analysis role.Note that education may be considered in lieu of experience and vice-versa.Experience in a baseball or sports-related environment is preferred.

Work Environment

Ability to work flexible hours, including evenings, weekends, and holidays as needed.Occasional travel may be required.Standard office working conditions with extended periods of sitting and working on a computer.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital, or veteran status, or any other protected status.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.

Why the UK Could Be the World’s Next AI Jobs Hub

Artificial Intelligence (AI) has rapidly moved from research labs into boardrooms, classrooms, hospitals, and homes. It is already reshaping economies and transforming industries at a scale comparable to the industrial revolution or the rise of the internet. Around the world, countries are competing fiercely to lead in AI innovation and reap its economic, social, and strategic benefits. The United Kingdom is uniquely positioned in this race. With a rich heritage in computing, world-class universities, forward-thinking government policy, and a growing ecosystem of startups and enterprises, the UK has many of the elements needed to become the world’s next AI hub. Yet competition is intense, particularly from the United States and China. Success will depend on how effectively the UK can scale its strengths, close its gaps, and seize opportunities in the years ahead. This article explores why the UK could be the world’s next global hub for artificial intelligence, what challenges it must overcome, and what this means for businesses, researchers, and job seekers.