Digital Marketing Manager: Growth & Analytics Lead

Groove; Kota Yogyakarta; Remote; IDR 2,686,246,000 - 3,760,745,000; Full time

Job summary

Groove, a distributed analytics leader, seeks a Remote Lead Sports Data Scientist to drive advanced analytics across our sports operations. You will design models, lead projects, and mentor junior data scientists, applying ML, statistics, and predictive analytics to improve performance, player development, and engagement.

This fully remote role requires 7+ years in data science with leadership experience, proficiency in Python or R, and strong data pipeline skills.

Qualifications

• 7+ years of professional experience in data science, with leadership or senior responsibilities.
• Strong background in statistical modeling and machine learning.
• Proficient in Python or R and data manipulation libraries.

Responsibilities

• Lead design, development, and evaluation of advanced statistical models and ML algorithms for sports analytics.
• Analyze large datasets to identify performance trends and actionable insights for athletes and coaches.
• Develop and maintain data pipelines and databases to support analytics.
• Mentor and guide a team of data scientists, fostering collaboration and research.
• Communicate findings clearly to stakeholders across the organization.
• Stay updated with the latest data science and sports analytics methods.

Skills

Leadership experience

Machine learning

Statistical modeling

Predictive analytics

Education

Master's or Ph.D. in Data Science, Statistics, Computer Science, or related field

Tools

Python

R

Pandas

NumPy

Job description

Remote Lead Sports Data Scientist

Our client is seeking an accomplished Remote Lead Sports Data Scientist to lead their advanced analytics team. This role is fully remote and will focus on leveraging sophisticated data science techniques to uncover insights that drive performance improvements across their sports operations. You will be responsible for designing and implementing data models, leading analytical projects, and mentoring junior data scientists. The ideal candidate has a strong background in statistical modeling, machine learning, and a passion for applying these skills to solve complex problems within the Leisure & Sports domain. Your work will directly influence player development, strategic decision-making, and fan engagement initiatives, making a significant impact from anywhere.

About the Role

Our client is seeking an accomplished Remote Lead Sports Data Scientist to lead their advanced analytics team. This role is fully remote and will focus on leveraging sophisticated data science techniques to uncover insights that drive performance improvements across their sports operations. You will be responsible for designing and implementing data models, leading analytical projects, and mentoring junior data scientists. The ideal candidate has a strong background in statistical modeling, machine learning, and a passion for applying these skills to solve complex problems within the Leisure & Sports domain. Your work will directly influence player development, strategic decision-making, and fan engagement initiatives, making a significant impact from anywhere.

Key Responsibilities

• Lead the design, development, and deployment of advanced statistical models and machine learning algorithms for sports analytics.
• Analyze large datasets to identify performance trends, predictive indicators, and actionable insights for athletes and coaches.
• Develop and maintain data pipelines and databases to support analytical needs.
• Mentor and guide a team of data scientists, fostering a collaborative and innovative research environment.
• Communicate complex findings and recommendations clearly to stakeholders across the organization, including technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and sports analytics methodologies.

Requirements

• Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related quantitative field.
• 7+ years of professional experience in data science, with at least 2 years in a leadership or senior role.
• Proven expertise in machine learning techniques, statistical modeling, and predictive analytics.
• Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
• Experience with