Data Scientist (вакансія неактивна)

We are looking for a mid-to-senior Data Scientist who is eager to proactively identify opportunities to improve and automate our business using data science and machine learning. You will work within a small, dedicated team of data scientists collaborating closely with backend engineers, other departments, and end users, while being part of a larger ecosystem of trading and technology experts.
In this role, you will design, develop, and optimize predictive models, implement anomaly detection systems, and participate in building production-grade machine learning solutions that directly impact trading and operational processes. You’ll also get hands-on experience with (or apply your existing knowledge of) high-performance architectures, including Kafka, serverless functions, databases, CI/CD pipelines, Kubernetes, and Docker.

Key Responsibilities:

Develop and refine mathematical and statistical models for predicting sports and e-sports outcomes.
Communicate with end users, collect feedback, and build technical solutions based on it.
Apply machine learning to improve trading strategies, automate workflows, and detect anomalies.
Proactively identify opportunities to use data science for business optimization and process automation.
Perform large-scale historical data analysis to generate insights and improve model performance.
Collaborate with backend engineers to build and maintain production machine learning systems.
Research and prototype new methods for expanding into new sports and markets.
KPIs for This Role
Delivery of production-ready machine learning models and pipelines for trading within agreed timelines.
Improvement in model accuracy and reliability, measured against established benchmarks.
Reduction of manual intervention in trading workflows through automation initiatives.

Requirements:

3+ years of experience in data science, analytics, or a related field.
Proficiency in Python (pandas, numpy, scikit-learn, etc.) and working with databases.
Strong knowledge of statistical modeling, probability, and machine learning techniques (Supervised Learning, Unsupervised Learning).
Experience with XGBoost/LightGBM.
Experience with large-scale data analysis and building actionable insights.
Ability to work collaboratively in a cross-functional team and communicate results clearly.

Nice-to-Have:

Experience in the sports or betting industry.
Experience with PyTorch/Tensorflow.
Familiarity with real-time data processing (Kafka, streaming systems).
Exposure to building data pipelines and integrating ML models into production systems.
Knowledge of advanced ML techniques (e.g., ensemble methods, time-series forecasting, anomaly detection).

What We Offer:

Work on high-impact projects in the fast-growing sports and e-sports betting industry.
A collaborative environment within a skilled team of data scientists and engineers.
Flexibility: Hybrid work with remote options.
Opportunities to shape our analytics and machine learning ecosystem and see your ideas implemented in production.