Senior ML Engineer

gamedistrict

Responsibilities

Lahore, Pakistan (On-site) 💼 Experience: 4–5+ Years 🛠️ Tech Stack: Python, SQL, Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, CatBoost, Cloud Data & ML Tools, MLOps About the Role GameDistrict is hiring a Senior ML Engineer / Data Scientist to build machine learning models that help us understand our players and improve our games.
You will own projects end to end, from problem framing and data exploration to production deployment and impact measurement.
You will work closely with product, marketing, and engineering teams, turning data into decisions across our mobile game portfolio.
You'll Do Design, build, and maintain predictive models on player behavior and engagement data.
Frame business questions as ML problems and define success metrics with stakeholders.
Engineer features from large-scale event and telemetry data.
training pipelines, scoring, monitoring, and retraining.
Design and analyze experiments to measure the impact of model-driven decisions.
Communicate findings and recommendations clearly to technical and non-technical audiences.
Mentor junior team members, review code and models, and help set ML best practices.
containers, workflow orchestration, experiment tracking, and model monitoring.

4–5+ years in data science or machine learning, with models shipped to production.
You'll Bring 4–5+ years of hands-on experience in data science or ML engineering, with at least 2 models you built running in production.
Proven work on user-level predictive modeling, such as classification, regression, or time-to-event problems.
Python (Pandas, NumPy, Scikit-learn) and advanced SQL on large datasets.
Deep experience with gradient-boosted trees (XGBoost, LightGBM, CatBoost) and solid grounding in statistics and probabilistic modeling.
Sound understanding of model evaluation, calibration, class imbalance, leakage, and validation on time-based splits.
A/B test design, statistical significance, and causal methods.
Ability to explain technical results to non-technical stakeholders and tie them to business metrics.
Bachelor's or Master's in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.