Senior Data Scientist

Working location: Remote full-time (09:00 - 18:00 ICT)

Salary range: USD 4,000 - 8,000 gross

RESPONSIBILITIES

We are looking for a senior applied data scientist or quantitative researcher to lead the development and continuous improvement of the predictive models and statistical frameworks behind our real-time forecasting engines, beginning with eSports. You will apply probabilistic modelling, machine learning and rigorous validation to live, high-frequency data, then work closely with our engineers to move that research into production.

You will join the Quantitative Research team, reporting to our CTO. Our Head Quantitative Strategist will guide research priorities and methodology. You will own the modelling approach and ongoing model performance. As you develop deeper domain and data expertise, you will take greater responsibility for development priorities and help shape the direction of future research.

●     Design, build and optimise the machine learning models and statistical frameworks that power our real-time eSports forecasting.

●     Extract deep predictive signals from raw, high-frequency data streams, starting with live eSports telemetry, turning complex in-game mechanics into structured modelling features.

●     Focus on model performance and probability calibration. Design rigorous backtesting frameworks to prevent data leakage and evaluate performance against historical forecasting benchmarks.

●     Build the probabilistic framework that turns live game-state and event-level predictions into consistent forecasts for game, round and match outcomes, score differences, aggregate game statistics and player performance.

●     Ensure your models are translated seamlessly into production-grade pipelines and microservices.

REQUIREMENTS

●     At least 5 years of professional experience in data science, quantitative research or statistical modelling, including ownership of complex modelling work.

●     Strong applied knowledge of probability and statistics, demonstrated through probabilistic modelling, calibration or comparable quantitative work.

●     Strong Python skills and experience writing clean, maintainable research and production code.

●     Proven experience designing rigorous backtesting or temporal validation environments, preventing data leakage and defining evaluation metrics for unusual business problems.

*** Nice to have

●     Experience applying probabilistic models in quantitative trading, market-making, forecasting, sports or eSports, particularly where calibrated probabilities have direct commercial value.

●     Experience modelling streaming data or other data that changes continuously over time.

●     Deep knowledge of competitive eSports, especially Counter-Strike 2, Dota 2 or League of Legends, including the underlying game mechanics and competitive meta.

●     An understanding of modern MLOps principles and experience with tools such as MLflow or Airflow.