Senior Data Engineer

Pentasia; United States; On-site; USD 100,000 - 130,000; Full time

Job summary

A leading gaming technology firm is seeking an exceptional Senior Sportsbook Data Science Engineer to lead advanced modeling initiatives in user profiling and risk control. This senior role offers full ownership of model strategy, hands-on development, and mentorship for junior data scientists. Ideal candidates have 5+ years of experience in machine learning within the Sportsbook or iGaming sector, and are proficient in Python and SQL. Responsibilities include developing predictive models and optimizing engagement strategies within a growing Sportsbook and iGaming ecosystem.

Qualifications

• 5+ years of machine learning experience in the Sportsbook or iGaming industry.
• Proven track record of delivering production ML solutions.
• Expert proficiency in Python and SQL, data wrangling, feature engineering.

Responsibilities

• Own the modeling roadmap for user profiling and risk strategy.
• Architect scalable ML pipelines and monitor production models.
• Develop user segmentation frameworks and classify user behaviors.

Skills

Machine learning experience

Modeling proficiency

Data analytics

Python

SQL

Communication skills

Model evaluation

Communication skills

Education

Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field

Job description

Senior Sportsbook Data Science Engineer – Pentasia

My client is seeking an exceptional Senior Sportsbook Data Science Engineer to lead advanced modeling initiatives that power user profiling, risk control, and personalized gaming experiences across their rapidly expanding Sportsbook and iGaming ecosystem.

This position is a senior, high‑impact role offering full ownership of model strategy, hands‑on development, and leadership of data science best practices. You will build and deploy machine learning models that directly influence product innovation, risk management, and operational effectiveness.

Key Responsibilities

• Own the end‑to‑end modeling roadmap for Sportsbook and iGaming user profiling, ensuring full alignment with business priorities, compliance needs, and risk strategy.
• Architect scalable ML pipelines for feature engineering, model training, deployment, and monitoring in production environments.
• Develop robust user segmentation and classification frameworks based on behavioral, transactional, and betting activity signals.
• Translate model insights into actionable strategy recommendations for cross‑functional teams including Product, Risk, Marketing, and Operations.
• Mentor and support junior data scientists/ML engineers, driving excellence in experimentation, deployment processes, and model governance.
• Build predictive models for user risk control coefficients (CCF) using behavioral, financial, and wagering‑related data features.
• Automate the assignment of CCF risk tiers and design differentiated risk‑control strategies per user segment.
• Continuously track model performance, detect drift, and optimize outcomes to support safer gaming, regulatory compliance, and risk‑aware decision making.
• Develop predictive models for user behavior, including betting propensity, churn risk, gameplay depth, and long‑term value forecasting.
• Build recommendation systems to personalise game/bet suggestions, promotions, and product experiences across Sportsbook and iGaming channels.
• Optimize personalisation frameworks to drive engagement, retention, and user lifetime value.

Qualifications

• 5+ years of hands‑on machine learning/modeling experience in the Sportsbook or iGaming industry, with a proven track record of delivering production ML solutions.
• Bachelor’s degree or above in Computer Science, Mathematics, Statistics, or a related quantitative field.
• Expert proficiency in Python and SQL, including data wrangling, feature engineering, model building, and evaluation.
• Deep knowledge of ML methods for classification, scoring, segmentation, recommendations, and behaviour prediction.
• Demonstrated experience deploying models into production, with strong understanding of monitoring, drift detection, and feedback loops.
• Excellent communication skills with the ability to convey complex modeling results to non‑technical stakeholders.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Analyst

Industries

Gambling Facilities and Casinos