Senior Data Scientist (m/f/x)

GRID esports; Lisboa; Presencial; EUR 60 000 - 90 000; Tempo integral

Resumo da oferta

GRID esports in Lisbon is seeking a senior data scientist to design and deploy real‑time predictive models for esports betting markets. You will work end‑to‑end from research through live deployment, translating in‑game mechanics into robust features and models.

Join a team that values probabilistic thinking, backtesting rigor, and production‑grade Python code. Experience with real‑time data streams and MLOps tools is highly desired.

Qualificações

• 5+ years of professional experience in data science, quantitative research, or statistical modeling.
• Deep, intuitive understanding of probability, statistics, and machine learning theory.
• Expert‑level skills in the Python data stack. You write clean, production‑grade code.
• Proven experience designing complex backtesting environments and defining custom evaluation metrics for unique business problems.

Responsabilidades

• Design, build, and optimise ML models and statistical frameworks powering real‑time odds and betting markets.
• Extract predictive signals from raw esports telemetry, converting game mechanics into features.
• Focus on model performance and calibration; design backtesting to prevent data leakage and compare to historical baselines.
• Create mathematical rules translating base win probabilities into derivative markets like handicaps and player props.
• Ensure models are production‑grade and integrated into scalable pipelines and microservices.

Conhecimentos

5+ years experience

Probability & stats

Python production code

Backtesting frameworks

Ferramentas

Python

MLFlow

Airflow

Descrição da oferta de emprego

• Are you excited about building ML systems that make predictions in real‑time?
• Are you driven by building things end‑to‑end, from research to live systems?

If the answers to the above questions are yes, then this role could be ideal for you! We are building real‑time prediction systems for competitive esports (CS2, Dota 2, League of Legends). Our models power live betting markets, producing continuously updated win probabilities, handicap lines, over/under totals, and specialty markets during matches.

Job Requirements

What you will do

• Design, build, and optimise the machine learning models and statistical frameworks that power our real‑time odds and betting markets
• Extract deep predictive signals from raw, high‑frequency 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 market baselines
• Create the mathematical rules and probabilistic derivations that translate baseline win probabilities into complex derivative markets (handicaps, totals, player props)
• Ensure your models are seamlessly translated into production‑grade pipelines and microservices

Your skills will include (must have)

• 5+ years of professional experience in data science, quantitative research, or statistical modeling
• Deep, intuitive understanding of probability, statistics, and machine learning theory
• Expert‑level skills in the Python data stack. You write clean, production‑grade code
• Proven experience designing complex backtesting environments and defining custom evaluation metrics for unique business problems

Nice to have

• Strong understanding of betting concepts, odds, overround, market‑making, or quantitative trading. You understand what it means to build models where calibrated probabilities directly drive revenue
• Experience modelling off streaming data or data that updates continuously over time
• Deep knowledge of competitive esports (CS2, Dota 2, LoL), the underlying game mechanics, and the competitive meta
• Understanding of modern MLOps principles and experience with tools like MLFlow, Airflow, etc.