Senior Data Scientist

GameDistrict is seeking a Senior Machine Learning Engineer / Data Scientist to join their team in Lahore, Pakistan. This on-site role requires 4 to 5+ years of experience in data science or machine learning, with a strong track record of deploying models into production. The successful candidate will be responsible for building predictive models that enhance player engagement and improve game experiences. You will manage projects end-to-end, collaborating closely with product, marketing, and engineering teams to translate data insights into actionable business decisions across a portfolio of mobile games.

Key Responsibilities

- Design, develop, and maintain predictive models focused on player behavior and engagement.
- Translate business challenges into machine learning problems and establish clear success metrics with stakeholders.
- Engineer features from large-scale event and telemetry datasets.
- Deploy models to production, including building training pipelines, scoring systems, monitoring, and retraining processes.
- Design and analyze experiments to evaluate the impact of model-driven decisions.
- Communicate technical findings and recommendations effectively to both technical and non-technical audiences.
- Mentor junior team members, review code and models, and contribute to establishing best practices in machine learning.

Required Qualifications

- 4 to 5+ years of hands-on experience in data science or ML engineering, with at least two models successfully deployed in production environments.
- Proven expertise in user-level predictive modeling, including classification, regression, or time-to-event analyses.
- Strong proficiency in Python, particularly with libraries such as Pandas, NumPy, and Scikit-learn, alongside advanced SQL skills for working with large datasets.
- Extensive experience with gradient-boosted tree algorithms such as XGBoost, LightGBM, and CatBoost.
- Solid foundation in statistics and probabilistic modeling, including model evaluation, calibration, handling class imbalance, preventing leakage, and validation using time-based splits.
- Practical knowledge of ML deployment and MLOps tools, including containerization, workflow orchestration, experiment tracking, and model monitoring.
- Familiarity with experimentation methodologies, including A/B test design, statistical significance, and causal inference techniques.
- Ability to clearly explain complex technical results to non-technical stakeholders and relate them to business outcomes.
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related discipline, or equivalent practical experience.

Preferred Qualifications

- Experience working in mobile gaming or other consumer-facing applications.
- Knowledge of real-time feature stores and low-latency model serving architectures.
- Exposure to deep learning techniques for sequential or behavioral data.
- Experience with distributed data processing frameworks such as Apache Spark.
- Contributions to the data science community through publications, Kaggle competitions, or open-source projects.

This role offers the opportunity to work at the intersection of gaming and advanced machine learning, driving impactful insights that shape player experiences. If you are passionate about applying your ML expertise to real-world problems and thrive in a collaborative environment, this position at GameDistrict could be an excellent fit.