Data Science Internship at PlaySimple Games Private Limited

About the Internship

Join PlaySimple Games as a Data Science Intern where you will actively contribute to crafting machine learning and data science solutions focused on player engagement, monetization strategies, experimental validation, and gaming analytics. In this role, you will perform detailed exploratory data analysis to uncover player patterns, trends, and potential product enhancements.

You will be responsible for building robust data pipelines and preparing datasets tailored for machine learning applications and experimental setups. Your tasks will also include supporting the design and statistical assessment of A/B testing frameworks, developing predictive models alongside senior data science professionals, and prototyping innovative AI tools utilizing large language models, agentic AI systems, and workflow automation solutions.

The internship involves working with Apache Spark to handle extensive datasets, creating dashboards and visual reports to share insights with product and game teams, and collaborating closely with cross-functional teams including product managers, engineers, and fellow data scientists to translate complex business challenges into data-driven approaches. Additionally, documenting experiments, models, and findings to enhance collective team knowledge and staying current with emerging developments in machine learning, AI, and data science are expected.

Candidate Eligibility and Requirements

• Must be pursuing a master's degree in computer science, AI, data science, statistics, mathematics, engineering, or a closely related discipline (undergraduate candidates are not eligible).
• Strong programming proficiency in Python is mandatory; experience with Apache Spark is advantageous.
• Academic or project background encompassing machine learning, statistics, probability theory, optimization, or data science is required.
• Exposure to large language models, generative AI, agentic AI, or AI workflow platforms is a significant plus.
• Familiarity with distributed data processing or big data ecosystems is preferred.
• Hands-on involvement in machine learning or AI through academic projects or open-source contributions is highly desirable.
• Possess strong analytical and problem-solving skills with enthusiasm for developing data-driven gaming products.
• An active gamer with a genuine interest in player behavior, game dynamics, and the mobile gaming sector is preferred.
• Self-motivated, curious, and ready to thrive in a fast-paced product development environment.
• Preference will be given to candidates with demonstrable GitHub projects, Kaggle participation, research papers, hackathon wins, competitive programming accolades, or notable AI/ML project experience.
• Excellent communication abilities and capability to work collaboratively within diverse teams.
• A strong eagerness to learn, experiment, and manage projects from conceptualization to deployment-ready prototypes.

Internship Details and Benefits

This is a six-month full-time in-office internship commencing immediately, with a stipend of INR 40,000 per month. The selected interns will receive a certificate upon completion, enjoy a relaxed dress code, benefit from a five-day workweek, and have access to complimentary snacks and beverages.

About PlaySimple Games

PlaySimple is recognized as India's rapidly expanding gaming company, established in 2014 with the aim of creating simple yet impactful social word games. Backed by SAIF Partners and IDG Ventures, the company boasts popular titles such as GuessUp and WordTrek, which collectively have exceeded 10 million downloads. Its portfolio includes successful games like Daily Themed Crossword, WordTrip, WordJam WordWars, and more, collectively engaging millions of players across platforms.

As part of the Sweden-based Modern Times Group (MTG), PlaySimple combines cutting-edge data, technology, and creativity to deliver world-class gaming experiences, fostering a culture rooted in innovation, ownership, and continual professional growth.