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Experience level:
More than 5 years
Education level:
Master
Languages:
Russian: Native
English: C1
– Explored trends and correlations in real estate and mortgage datasets using Python and SQL to detect underlying risk variables.
– Constructed behavioral scoring models by applying feature engineering techniques to enhance prediction of customer default using Python and SQL.
– Enhanced predictive accuracy by 10% by retraining scoring models on expanded and segmented real estate and mortgage lending datasets, utilizing Python and machine learning libraries.
– Compiled comprehensive documentation outlining methodologies and processes underlying data models using MS Office and LaTeX.
– Developed and backtested algorithmic trading strategies using the QuantConnect platform.
– Developed and executed simulations for varying asset allocations in Python to evaluate risk-return outcomes before implementing adjustments.
– Engineered and refined strategy logic through iterative A/B testing of different model versions.
– Implemented automated Python scripts to produce daily investor performance reports, utilizing Pandas to streamline data extraction and reporting processes.
– Gathered and synthesized regional construction market data using SQL tools to support company expansion decisions.
– Prepared summary reports and visual dashboards in Tableau to communicate supplier comparisons to stakeholders effectively.
– Reduced time of recurring calculation tasks through custom Python functions to reduce errors.
– Generated reports and presentations using MS Office and Tableau for internal and external interactions.
– Python: Pandas, NumPy, SciPy, Matplotlib, TensorFlow.
– SQL: MS SQL, PostgreSQL.
– C++: Pthreads.
– Data Visualization (BI): Tableau, Power BI, MS Office, LaTeX.
– English: Advanced. Russian: Native.
– Statistics, Calculus, Geometry.