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@dariarusakova
I am a data scientist optimizing products with analytics, automation, A/B testing, and dashboards.
I am a data scientist with hands-on experience driving product improvements through analytics and automation. At Sberbank I automated log aggregation with SQL and built Tableau dashboards to track GMV, DAU/MAU, churn, retention and conversion metrics.
I focus on turning data into product outcomes: I increased user conversion by streamlining funnels, simplified UI flows, introduced prefilled fields via integrations, and ran A/B tests for new features. I also replaced bootstrap-based estimation with the delta method to improve statistical accuracy.
Previously I worked as a QA Engineer leading automation for a Mutual Investment Fund product, automating four functional subsystems end-to-end and reducing testing time from one month to 15 minutes while lowering defective builds. I automated UI testing with a device farm and helped scale tests for other teams.
I hold a Master’s-level computer science background and built a diploma project: a financial assistant using RAG, LSTM, GPT and Streamlit to predict stock movements and provide company and peer analysis. I mentor juniors, design testing and analytics processes, and deliver practical, measurable results.
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Work history, roles, and key accomplishments
Sberbank
May 2019 - Jan 2023 (3 years 8 months)
Led testing and automation for a Mutual Investment Fund product across Web/Mobile/iPad, automating four functional subsystems to reduce testing time from one month to 15 minutes and lower defective builds.
Sberbank
Jan 2023 - Present (2 years 10 months)
Automated log aggregation with SQL to compute GMV, DAU/MAU, churn and retention; streamlined product funnel and UI to increase user conversion and ran A/B tests to validate features.
Degrees, certifications, and relevant coursework
Master's degree, Computer Science
2023 - 2025
Grade: GPA 8.8
Activities and societies: Core: Algorithms, Discrete Mathematics, Linear Algebra. Data analysis: SQL, Time series, Statistics, Probability Theory. Machine learning: NLP, Deep Learning. Project tools: RAG, LSTM, GPT, Streamlit.
Master's thesis developed a financial assistant that predicts stock prices and provides company and peer financial overviews using RAG, LSTM, GPT, and Streamlit.
Bachelor's degree, Economic Sciences
2015 - 2019
Bachelor's thesis analyzed the sustainability of a commercial bank during crisis periods and predicted the likelihood of license revocation using logistic regression and RandomForest.
Data Analyst Certificate, Data Analysis
2022 -
Activities and societies: Projects: analysis of app installations, unit-economics for online shops, RFM analysis, A/B tests, dashboards. Skills: SQL (ClickHouse, PostgreSQL), API usage, Python (Jupyter), Airflow DAGs.
Completed a Data Analyst course with projects in app installation analysis, unit-economics for online retail, RFM segmentation, A/B testing, and dashboard creation.
Software and tools used professionally
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