What if every player experienced the right challenge, reward or offer at the right moment? We are looking for a Senior Data Scientist to build the intelligence behind those decisions. You will translate rich gameplay and player-behavior data into machine learning solutions that improve player experience, engagement, retention and sustainable monetization.This is a hands-on, high-ownership role - identify the opportunity, build the model, validate its incremental impact and partner with Product and Engineering to bring it into the game.PROBLEMS YOU WILL HELP SOLVE : - Personalization & recommendations - Recommend relevant challenges, rewards, offers and in-game experiences using player behavior, context and preferences; Churn prediction & retention - Detect early signs of disengagement, understand why players leave and develop models that help target meaningful retention interventions.- Player economy & monetization - Find opportunities across virtual currency, game modes, in-app purchases and ads while balancing monetization with healthy gameplay and player experience.- WHAT YOU WILL OWN : - End-to-end applied ML - Frame product questions as measurable ML problems; develop features, train and evaluate models, and help operationalize scoring or recommendations.- Rigorous measurement - Choose suitable offline and online metrics; address rare outcomes, data leakage, bias, calibration and model drift; Cross-functional delivery - Partner closely with Product, Game Design, LiveOps, Analytics and Engineering to turn models into decisions,



features and measurable results.- Explicit communication - Explain trade-offs, insights and recommendations to both technical and non-technical stakeholders; help shape the data science roadmap.WHAT WE ARE LOOKING FOR : - Experience - 4+ years in data science or applied machine learning, with evidence of taking models beyond notebooks into real product or business decisions.TECHNICAL STRENGTH : - Strong Python and SQL skills; practical experience with feature engineering, supervised learning, model evaluation and libraries such as scikit-learn, XGBoost/LightGBM, PyTorch or TensorFlow.- Statistical judgment - Solid grounding in probability, statistics, experimentation and interpreting model performance for imbalanced classification, ranking or regression problems.- Execution mindset - Comfort working with large behavioral/event datasets, ambiguous problems, iteration, version control and cloud environments such as AWS, Azure or GCP.- Product curiosity - An ability to connect technical results to player behavior, user experience and measurable business impact.GREAT TO HAVE : - Domain experience - Free-to-play/mobile gaming, consumer apps, recommendations, churn prevention, payer propensity, LTV forecasting or lifecycle marketing.- Advanced methods - Recommender systems, uplift modeling, contextual bandits, reinforcement learning, causal inference, deep learning or production ML/MLOps.- Emerging technologies - Interest in applying LLMs or agentic AI to meaningful analytics or player-experience problems. (

📌 Senior Data Scientist - Machine Learning, AI (Bengaluru)
🏢 BULWARK GLOBAL SERVICES
📍 Bengaluru