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nataljatalikova/README.md

Quantitative Finance & Data Science Specialist | MSc Birkbeck

📍 London, UK | 😄 Pronouns: She/Her

👋 About Me

I am a data professional operating at the intersection of Quantitative Finance and Machine Learning. My approach bridges the gap between academic rigour (MSc from Birkbeck, University of London) and over a decade of commercial project management experience.

I specialise in building robust and interpretable predictive models, with a particular focus on Credit Risk, Statistical Learning, and ESG-driven analytics. I thrive in environments that require both high-level strategic thinking and granular data engineering.

🧠 Focus Areas

  • 📊 Financial Risk Modelling (Market/Credit), Time Series Analysis, Financial Econometrics
  • 🧮 Pursuing clarity and reproducibility in analytical data pipelines
  • 🌱 ESG-related projects involving statistical modelling, data analytics, and machine learning

🛠 Technical Background

Languages:
Python, R, SQL

Databases:
PostgreSQL

Environments:
Jupyter Notebook, RStudio, VS Code

Data Analysis & Statistics

  • Python libraries:
    pandas, NumPy, scikit-learn, SciPy, XGBoost, TensorFlow

  • R libraries:
    caret, e1071, xgboost, pROC, themis, recipes

Visualisation:
matplotlib, seaborn, ggplot2

BI & Reporting:
Power BI

Version Control:
Git, GitHub

🌿 Interests

  • Sustainable finance & ethical technology
  • Data visualisation & storytelling
  • Restorative practice, yoga, and fine arts

🔗 Portfolio & Contact

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  1. Automotive-Loan-Default-Prediction Automotive-Loan-Default-Prediction Public

    Financial Data Science project, Python

    Jupyter Notebook 1

  2. nataljatalikova nataljatalikova Public

    It is my self-presentation.

  3. Statistical-Learning-with-R Statistical-Learning-with-R Public

    R Experiments and reports for Birkbeck MSc Quantitative Finance with Data Science SLc module, 2025.

    R

  4. SQL-PBI-hpi-mortgage-lags SQL-PBI-hpi-mortgage-lags Public

    End-to-end analysis of UK housing prices and mortgage rates using SQL data marts and Power BI. Includes feature engineering, lagged correlation, and regional insights. Visualizes key analytical fin…

    1

  5. msc-tail-risk-aware msc-tail-risk-aware Public

    Reproducible research project extending an MSc study into the Bear Miss Rate (BMR) framework downside forecast evaluation, with BMR, BMR_tol, BMR_Z and corrected common-panel results for five UK en…

    Jupyter Notebook