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Senior Machine Learning Engineer, Warsaw

Client:

Sigma Software

Location:

Warsaw, Poland

Job Category:

Other

EU work permit required:

Yes

Job Reference:

0deef958b126

Job Views:

7

Posted:

23.01.2025

Expiry Date:

09.03.2025

Job Description:

• Collect, clean, and preprocess historical financial data, extracting meaningful features such as moving averages, RSI, and volatility indicators to enhance model performance.
• Design and train predictive models (e.g., LSTM, XGBoost, Random Forests) with rigorous backtesting, hyperparameter tuning, and evaluation using metrics such as Sharpe Ratio, Sortino Ratio, and Maximum Drawdown.
• Deploy models in production environments, monitor performance, address data drift through retraining, and collaborate with teams to integrate insights into trading systems while maintaining thorough documentation.

Qualifications:

• At least 5 years of experience in Machine Learning or AI-related roles with a focus on financial data modeling, quantitative analysis, or algorithmic trading systems.
• Proficiency in Python, with hands-on experience using libraries such as TensorFlow, PyTorch, scikit-learn, and XGBoost.
• Familiarity with big data frameworks (e.g., Spark, Dask) and cloud platforms like AWS or GCP.
• Proven track record of developing and deploying trading models or financial strategies.
• Strong experience in time-series forecasting, financial data analysis, and feature engineering for stock market data, including technical indicators and sentiment analysis.
• Expertise in hyperparameter tuning techniques, model optimization, and performance enhancement.
• Solid foundation in statistics, probability, and optimization methods, with knowledge of risk management metrics such as Sharpe Ratio, Alpha, and Beta for portfolio optimization.
• At least an Upper-Intermediate level of English.

WILL BE A PLUS:

• Experience in proprietary trading, hedge funds, or asset management firms.
• Knowledge of trading platforms such as Interactive Brokers, Alpaca, or similar systems.
• Knowledge of options pricing, derivatives, or quantitative trading strategies.
• Familiarity with alternative data sources, including news sentiment, social media trends, and other non-traditional datasets for market analysis.
• Experience with transformer models (both language and visual).
• Hands-on experience with backtesting tools like Zipline or Backtrader.
• Familiarity with Docker, Kubernetes, and CI/CD pipelines for scalable model deployment.

Additional Information:

PERSONAL PROFILE:

• Strong critical thinking and problem-solving skills, with the ability to assess and challenge model assumptions.
• Excellent communication skills for presenting complex concepts.
• Ability to work both independently and collaboratively in fast-paced, dynamic environments.

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