Data Scientist

Next Ventures; California (MO); On-site; USD 90,000 - 120,000; Full time

Job summary

A company in the sports and entertainment sector is seeking an experienced Data Scientist to lead the development of advanced analytics solutions. This role involves designing machine learning models to enhance venue operations and fan experiences, utilizing massive datasets. Ideal candidates should have expertise in predictive modeling and strong programming skills in Python or R.

Qualifications

• Experience in machine learning for large datasets.
• Strong proficiency in Python or R for data analysis.
• Ability to design algorithms and build predictive models.

Responsibilities

• Design identity resolution systems using matching algorithms.
• Develop predictive models for fan behavior.
• Build real-time scoring engines for dynamic pricing and marketing.
• Create anomaly detection systems for crowd management.
• Implement feature engineering pipelines for data processing.
• Design experimentation frameworks to measure initiative impact.

Skills

Machine Learning

Data Analysis

Predictive Modeling

Anomaly Detection

Tools

Python

R

SQL

Job description

I am partnered with a company who are currently looking to hire a experienced Data Scientist to join their Data Platform team and lead the development of advanced analytics solutions for identity resolution and predictive modeling in the sports and entertainment venue space.

You will build sophisticated probabilistic and deterministic matching algorithms to create unified fan profiles across millions of touchpoints while developing predictive models that enhance venue operations and fan experiences. In this role, you will design and implement machine learning models that power real-time decision-making for crowd management, personalized fan experiences, and revenue optimization. Working with massive datasets from ticketing systems, mobile apps, in-venue sensors, and third-party platforms, you'll deliver actionable insights that transform how venues understand and engage with their audiences.

Responsibilities

• Design and implement identity resolution systems combining deterministic and probabilistic matching algorithms to unify fan profiles across multiple touchpoints
• Develop predictive models for fan behavior including attendance prediction, purchasing patterns, and personalization using advanced ML techniques
• Build real-time scoring engines for dynamic pricing, targeted marketing, and operational optimization
• Create anomaly detection systems for crowd management and security using streaming venue sensor data
• Implement feature engineering pipelines processing billions of events from ticketing, POS, mobile apps, and IoT devices
• Design experimentation frameworks including A/B testing and causal inference to measure impact of venue initiatives