Описание
We are looking for a Machine Learning Researcher to design, develop, and evaluate predictive models for financial markets. You will work at the intersection of quantitative research, machine learning, and real-world trading constraints, contributing to alpha generation and risk modeling.
Responsibilities
Develop and validate machine learning models for financial time series and cross-sectional data Conduct research on alpha signals, feature engineering, and predictive modelling techniques Design experiments and backtesting frameworks with proper statistical rigor Work with large-scale structured and unstructured financial datasets Collaborate with engineering teams to deploy models into production pipelines Analyze model performance, stability, and robustness under changing market conditions Improve data pipelines, labeling strategies, and evaluation methodologies
Requirements
3+ years of relevant experience Strong Python skills and experience with ML ecosystems (AWS Sagemaker, MLFlow) Hands-on experience working with tabular/time series data with usage of ML Solid understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation Overfitting, regularization, cross-validation Knowledge of statistical methods and probability theory Experience with experiment design and offline evaluation Ability to work with large datasets and build efficient data processing pipelines Familiarity with SQL and data querying Strong analytical and problem-s
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