🎓 Data Science Graduate Student @ Duke | 🤖 AI Explainability & Causal ML | 📊 Data-Driven Decision Making
I am a data scientist with expertise in machine learning, causal inference, NLP, and statistical experimentation. My work bridges the gap between AI interpretability, data-driven business decisions, and real-world applications.
🔍 Passionate about explainable AI, ethical ML, and disinformation research
📈 Strong background in data analytics, experimentation, and machine learning
🎵 Enthusiast in network analysis and data visualization
🔹 Duke University (Aug 2023 – May 2025)
M.S. in Interdisciplinary Data Science
- Coursework: Machine Learning, Deep Learning, NLP, Causal Inference, Bayesian Statistics, Data Engineering
🔹 Higher School of Economics, Moscow
B.S. in Political Science (Quantitative Methods major, Applied Statistics minor)
- Coursework: Data Analysis, Machine Learning, Econometrics, Advanced Statistical Modeling
- Recipient of Federal full-tuition scholarship
- Nominee for Presidential Grant in Science
🔹 Web Data Scientist @ ROI Revolution
- Developed machine learning models (Gradient Boosting, SHAP) to optimize eCommerce conversion rates
- Designed A/B testing frameworks (sequential, Bayesian) and analyzed 100+ experiments
- Built data pipelines using Google Analytics API & BigQuery for enhanced business intelligence
🔹 Middle Data Analyst @ Tinkoff Bank
- Led the development of BI dashboards for executive decision-making
- Conducted statistical experimentation to reduce client loss, saving ~$700K/month
- Built a real-time payment prediction ML model for Fintech workflows
💻 Languages: Python, SQL, Rust, VBA, R
📊 Data Science & ML: Scikit-Learn, TensorFlow, PyTorch, NLP, Bayesian Statistics
📈 Visualization & Analytics: Plotly, Dash, Tableau, Google Data Studio
⚡ Experimentation: A/B Testing (Bayesian, Frequentist, Sequential), UX Testing
📧 anastasiia.saenkoduke@gmail.com
🔗 GitHub | LinkedIn | Portfolio