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Data Scientist - Baseball Analytics Baseball Sciences

Chicago Cubs

Job Overview

Location

Chicago, IL

Job Type

Full-time

Full Job Description

📋 Description

• Shape the future of Cubs baseball by building next-generation analytical models that directly influence player acquisition, development, and in-game strategy for one of the most storied franchises in sports history.
• Own end-to-end data pipelines that ingest, clean, and transform raw baseball data into actionable intelligence, ensuring every coach, scout, and executive has the freshest, most reliable metrics at their fingertips.
• Specialize in a high-impact domain—pitching, position-player evaluation, major-league strategy, amateur scouting (domestic or international), professional evaluation, model QA/validation, or AI innovation—and become the go-to expert whose insights move the win curve.
• Conduct rigorous quantitative research that uncovers hidden value in players, strategies, and market inefficiencies, then translate complex findings into clear, compelling narratives for coaches, front-office leadership, and ownership.
• Collaborate daily with the Baseball Systems team to deploy new models and interactive visualizations into Cubs web applications, ensuring seamless integration with scouting reports, coaching dashboards, and fan-facing products.
• Partner with stakeholders across Baseball Operations to prioritize research roadmaps, balance quick-win requests against long-term strategic initiatives, and continuously refine the organization’s analytical priorities.
• Design automated processes that detect data-quality anomalies and model drift in real time, safeguarding the integrity of every projection and recommendation that reaches the dugout or the draft room.
• Present findings in written briefs, slide decks, and live workshops, tailoring depth and language to audiences ranging from data-savvy analysts to field staff who think in batting averages and spin rates.
• Experiment with emerging technologies—computer vision, wearable sensor data, biomechanical tracking, natural-language scouting notes—to push the Cubs to the forefront of baseball science.
• Contribute to a culture of intellectual curiosity, healthy debate, and continuous learning by leading internal seminars, peer-reviewing teammates’ code, and mentoring junior analysts.
• Travel periodically to Mesa for Spring Training or to affiliate ballparks to gather context, validate models against live observations, and strengthen relationships with coaches and players.
• Uphold the highest standards of confidentiality and integrity when handling proprietary data, ensuring competitive advantages remain within the Cubs family.

🎯 Requirements

• Proficiency with SQL and at least one data-analysis programming language (Julia, MATLAB, Python, or R)
• Strong foundation in statistical modeling, machine learning, and data visualization
• Advanced degree or comparable work experience in a quantitative discipline
• Excellent written and verbal communication skills, able to explain technical concepts to non-technical audiences
• Demonstrated ability to work collaboratively within a team setting
• Prior experience or knowledge of baseball analytics and technologies (preferred)

🏖️ Benefits

• On-site parking and transit benefits
• Paid time off—personal, sick, vacation, office holidays, and winter break
• Flexible work arrangements and casual dress code
• Complimentary meal & beverage plan plus Cubs home-game and spring-training ticket allotment
• 401(k) with employer match, medical/dental/vision/life insurance, and tuition reimbursement

Skills & Technologies

Python

Spring

REST

Data Science

Remote

$65k-$115k

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Chicago Cubs

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About Chicago Cubs

The Chicago Cubs are a professional Major League Baseball (MLB) team based in Chicago, Illinois. They compete in the National League Central Division. Their home stadium is Wrigley Field, located on Chicago’s North Side. The Cubs have a storied history dating back to the 19th century, and they won the World Series in 2016, ending a 108-year championship drought.

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