Data Scientist

What you will do: • Develop and deploy machine learning and statistical models for forecasting, pattern recognition, and financial analytics.

• Work with structured and unstructured datasets including market data, alternative datasets, and event-driven information sources.

• Design and maintain scalable data preparation and feature engineering workflows.

• Conduct rigorous backtesting, validation, and performance analysis to evaluate model robustness and reduce overfitting risk.

• Identify proprietary indicators and predictive features that improve analytical accuracy and signal quality.

• Collaborate closely with cross-functional stakeholders to translate technical findings into commercially meaningful insights.

• Continuously evaluate data integrity, model assumptions, and research methodologies to maintain high analytical standards.

What you will need: • Bachelor’s or Master’s degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Physics, Financial Engineering, or a related field.

• 2+ years of experience working with large-scale analytical or financial datasets.

• Strong foundation in statistics, probability, machine learning, and quantitative analysis.

• Familiarity with financial markets, trading concepts, or investment data is advantageous.

• Advanced proficiency in Python, including common data science and machine learning libraries (e.g. Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow).

• Strong SQL and data querying capabilities.

• Experience handling high-volume or real-time datasets is a plus.

• Strong critical thinking skills with a detail-oriented and hypothesis-driven approach to problem solving.