Lead Data Scientist

PlaySimple Games; Bengaluru; On-site; INR 2,600,000 - 3,800,000; Full time

Job summary

PlaySimple Games in Bengaluru is seeking a Lead Data Scientist to drive AI and decision science initiatives across our gaming portfolio. You will own projects from ideation to production, mentoring junior data scientists and shaping best practices within the team.

You will build models for personalization, live ops, monetization, and player engagement, while collaborating with product managers, engineers, and analysts to deliver measurable business impact.

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Artificial Intelligence, Data Science, Engineering, or a related field.

Responsibilities

• Build ML models for personalization, recommendations, LiveOps, monetization, and player engagement.
• Design and analyze experiments using robust statistical methodologies.
• Develop predictive models including player segmentation, churn prediction, LTV estimation, and revenue forecasting.
• Apply optimization techniques to improve player experiences and business outcomes.
• Translate business problems into scalable AI solutions.
• Build production-ready ML pipelines with engineering teams.
• Partner with Product and Engineering to evaluate business impact.
• Stay current with advances in AI, Machine Learning, and Decision Science.

Skills

Python programming

SQL programming

Statistical analysis

Machine Learning

Communication skills

Education

Bachelor's or Master's degree in Computer Science / Statistics / Mathematics / AI / Data Science / Engineering

Tools

Apache Spark

n8n

Cloud ML environments

Job description

Lead Data Scientist – AI & Decision Science

Work Location & Policy

This role requires working from our Bengaluru office five days a week (Monday–Friday). We are not considering remote or hybrid arrangements for this position.

Job Summary

We are looking for a Lead Data Scientist to build intelligent, data-driven products that improve player experience and business performance across our gaming portfolio. You will work closely with Product Managers, Engineers, and Analysts to solve challenging business problems using statistics, optimization, experimentation, and Machine Learning. You will own projects from ideation through production deployment while mentoring junior data scientists and helping establish best practices across the team.

Responsibilities

• Build Machine Learning models supporting personalization, recommendations, LiveOps, monetization, and player engagement.
• Design and analyze experiments using robust statistical methodologies.
• Develop predictive models including player segmentation, churn prediction,LTV estimation, and revenue forecasting.
• Apply optimization techniques to improve player experiences and business outcomes.
• Translate business problems into scalable AI solutions.
• Build production-ready ML pipelines together with engineering teams.
• Partner with Product and Engineering to evaluate business impact.
• Stay current with advances in AI, Machine Learning, and Decision Science.

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics,Artificial Intelligence, Data Science, Engineering, or a related field.

Requirements

• 5–8 years of experience in Data Science or Applied Machine Learning.
• Strong product experience in Gaming, Consumer Internet, E-commerce,Marketplace, or Decision Science platforms.
• Demonstrated experience deploying Machine Learning solutions into production.

Strong understanding of:

• Statistics
• Bayesian Methods
• Optimization
• Predictive Modeling

• Experience working with Apache Spark.
• Strong conceptual understanding of Agentic AI, LLM applications, and workflow automation tools such as n8n.
• Strong Python and SQL programming skills.
• Experience working with cloud-based ML environments.
• Excellent communication and collaboration skills.
• An avid gamer with a passion for understanding player behaviour and game mechanics.

What We Look For

• Strong analytical thinking.
• Excellent problem-solving ability.
• Ownership and execution focus.
• Ability to collaborate across teams.
• Passion for learning emerging AI technologies.
• Comfortable working in a fast-paced product environment.