Raisa Dzhamtyrova, PhD
Verified Expert in Engineering
Machine Learning Developer
Raisa is a seasoned full-stack data scientist with over six years of expertise in developing and deploying machine learning models. She has a PhD in machine learning, with several publications in leading journals. Raisa is highly skilled in utilizing a diverse set of technologies, including Python (Polars, pandas, NumPy, scikit-learn, LightGBM, XGBoost, PyTorch), R, SQL, Flyte, Git, Databricks, MLflow, and AWS.
Portfolio
Experience
Availability
Preferred Environment
Python 3, R, SQL, Scikit-learn, Machine Learning, Polars, Pandas, NumPy, PyTorch, XGBoost
The most amazing...
...project I've developed is a new method of aggregating anomaly detection algorithms that improved the cybersecurity practices of digital identity providers.
Work Experience
Data Analyst | Scientist
RVA Energy LLC
- Developed forecasting models for energy futures using various statistical, machine learning, and deep learning techniques. Used unsupervised learning to identify outliers in the data to build a more robust model.
- Worked on models that improved on the existing approach by a few percentage points in terms of various metrics (MAE, RMSE, and sMAPE) and contributed to the financial portfolio decision-making and risk management.
- Built reproducible machine learning pipelines using Flyte, a cloud native platform for data processing. This allowed the automation of the entire data science workflow from data ingestion to model training and deployment.
- Implemented the models on AWS, allowing for scalable and efficient deployment. Docker was used to containerize the models and their dependencies. The implemented models re-train daily using the latest data, ensuring they are up-to-date.
Computer Science Lecturer
Royal Holloway, University of London
- Conducted and published research focused on probabilistic prediction and ensemble methods. Presented the work to help attract collaboration from the industry.
- Taught CS database systems (SQL/PostgreSQL) to MSc students and supervised final-year projects.
- Co-organized research seminars on advanced topics in Big Data.
Postdoctoral Research Associate
The Alan Turing Institute
- Collaborated with digital identity providers to improve their cybersecurity practices.
- Conducted research in identifying anomalous activity that later was used by identity providers. The research was published in Springer.
- Presented my work at conferences, providing more exposure to the project and attracting more collaboration.
Teaching Assistant
Royal Holloway
- Assisted with CS Data Analysis, Machine Learning, and Data Visualization MSc courses. Taught various machine learning courses, including supervised/unsupervised shallow and deep learning.
- Marked the assignments and prepared the coursework materials.
- Provided supervision for final-year MSc students. Helped students with issues on their dissertations.
Data Scientist
Lindgren Laboratories Limited
- Developed models for the prediction of outcomes of football matches in online mode using statistical and machine learning methods in R and Python.
- Improved the existing model and state-of-the-art methods, which increased revenue by several percentage points.
- Managed one of the team members by guiding his work and supervising project timelines.
Chief Risk Specialist | Data Scientist
Promsvyazbank
- Developed new methods for collection, fraud, and application risk models that improved the bank collection strategies and decreased loan default rates.
- Helped increase collaboration between the risk and the collection departments, leading to an improved risk-based collection strategy.
- Performed mathematical and financial analyses for the risk committee and senior management, affecting the bank's future policies.
Risk Analyst
National Bank TRUST
- Improved the bank's marketing campaigns through efficient client segmentation by applying unsupervised clustering methods.
- Developed credit and fraud detection scoring models, decreasing the default and fraud rates on the bank's loans.
- Delivered various analytics reports on the financial situation at the time, which helped to guide the department's strategies.
Experience
LLM-powered application consulting
Competitive Online Algorithms for Probabilistic Prediction
https://www.researchgate.net/profile/Raisa_Dzhamtyrova/researchOpen-source Contributions
https://github.com/pandas-dev/pandas/commits?author=raisadzDeploying a Machine Learning Model on Heroku with FastAPI
https://github.com/raisadz/deployment_projectReal-time Anomaly Detection
https://github.com/alan-turing-institute/anomaly_with_expertsI created a new approach for aggregating unsupervised anomaly detection algorithms, which is to be used by digital identity provider companies and I developed the prototype in Python. The preprint is available at arxiv.org/pdf/2010.03857.pdf
Building ML Pipeline for Short-term Rental Prices in NYC
https://github.com/raisadz/build-ml-pipeline-for-short-term-rental-pricesDynamic Risk Assessment System
https://github.com/raisadz/model_diagnosticsDynamic Cyber Risk Estimation
https://github.com/alan-turing-institute/dynamic_cyber_riskSkills
Languages
Python 3, R, SQL, Python, Excel VBA, Bash Script, SAS
Frameworks
Data Lakehouse, Apache Spark, LightGBM, Flask, Streamlit
Libraries/APIs
Scikit-learn, Matplotlib, NumPy, Pandas, XGBoost, PyTorch, PySpark, TensorFlow, REST APIs
Tools
Git, Jupyter, Boto 3, Microsoft Excel, Spreadsheets, StatsModels, AWS CloudTrail, Amazon QuickSight, Amazon Athena, Pytest, Tableau, Cron, Amazon Elastic Container Registry (ECR)
Paradigms
Data Science, Testing, Quantitative Research, Automation, Anomaly Detection, Unit Testing, ETL
Platforms
Databricks, Amazon EC2, Docker, Weights & Biases, Amazon Web Services (AWS), Linux, Azure, Heroku
Storage
Databases, PostgreSQL, MySQL, Amazon S3 (AWS S3), Data Pipelines
Other
Machine Learning, Visualization, Real-time Data, Risk Models, Credit Risk, Finance, Deep Learning, Data Analysis, Data Visualization, Ensemble Methods, Predictive Modeling, Predictive Analytics, Time Series, Time Series Analysis, Regression Modeling, Classification, Regression, Statistical Analysis, Version Control, Statistics, Research, Technical Writing, Statistical Modeling, Data Analytics, Predictive Learning, Linear Regression, Big Data, Data Reporting, Financial Modeling, Risk Analysis, Polars, Artificial Intelligence (AI), Forecasting, Statistical Data Analysis, Data Engineering, Production, Deployment, Security, HyperOpt, Azure Databricks, Analytics, Data Manipulation, Data Scientist, Logistic Regression, Excel 365, Unsupervised Fraud Detection, Unsupervised Learning, Outlier Detection, Mathematics, Risk, Economics, Financial Data, Sports, Software Engineering, MLflow, CI/CD Pipelines, Amazon Machine Learning, Flyte, Futures & Options, Trading, Quantitative Finance, Generative AI, GitHub Actions, FastAPI, DVC, Machine Learning Operations (MLOps), Data Modeling, Consulting, ChatGPT, Large Language Models (LLMs), LangChain, OpenAI GPT-4 API, OpenAI GPT-3 API, OpenAI
Education
PhD in Machine Learning
Royal Holloway, University of London - Egham, United Kingdom
Master's Degree (Outstanding Thesis Award) in Computational Finance
Royal Holloway, University of London - Egham, United Kingdom
Master's Degree in Applied Mathematics and Physics
Moscow Institute of Physics and Technology - Moscow, Russia
Bachelor's Degree in Applied Mathematics and Physics
Moscow Institute of Physics and Technology - Moscow, Russia
Certifications
Databricks Certified Machine Learning Professional
Databricks
Machine Learning DevOps Engineer
Udacity
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