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Open to UK fintech / fraud-analytics roles
🟢
Open to UK fintech / fraud-analytics roles
  • Wildberries
  • London, UK
  • 20:38 (UTC +01:00)
  • LinkedIn in/rymarmary

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rymarmary/README.md

Hi, I'm Mary 👋

Data Analyst with 3+ years of experience focused on fraud and behavioural analytics. Currently at Wildberries (Russia's largest online retailer, 200M+ MAU), evaluating fraud and anti-bot scoring models, designing behavioural alerts, and applying graph methods to investigate user connections.

🔍 Currently: open to UK fintech / fraud-analytics roles
📍 Location: London, UK (work-eligible, no sponsorship needed)
💼 Reach me: LinkedIn

Featured projects

Project What it shows
network-cluster-analysis Graph methods (centrality, community detection) — transferable to fraud network analysis
digital-focus Full-stack web app with custom event analytics pipeline (ClickHouse + serverless API)
mobile-listing-ab-test A/B test analysis with proper statistical testing by metric distribution
financial-behavior-tech-professionals Independent research: survey design → analysis → publishing

Stack

Languages: Python, SQL Data: pandas, NumPy, scikit-learn, NetworkX, igraph, statsmodels, scipy
Databases: ClickHouse, PostgreSQL, MySQL
BI: Superset, Redash, Power BI, Yandex DataLens
Pipelines: Airflow

Pinned Loading

  1. network-cluster-analysis network-cluster-analysis Public

    Graph analysis of a communication network — centrality, community detection, applicable to fraud network investigation

    Jupyter Notebook 1

  2. digital-focus digital-focus Public

    Full-stack web app with custom event analytics pipeline (Next.js → ClickHouse → SQL). Demonstrates end-to-end product analytics without external SaaS

    TypeScript 3

  3. financial-behavior-tech-professionals financial-behavior-tech-professionals Public

    Independent research: where does the salary go? Survey of 75 tech professionals on income, spending, and financial comfort

    Jupyter Notebook 1

  4. mobile-listing-ab-test mobile-listing-ab-test Public

    A/B test take-home: visit → order conversion analysis on a travel marketplace, with statistical testing and product recommendations

    Jupyter Notebook 1