Роман Слаутин - Резюме Аналитик данных

Work Experience — 8 years 9 months July 2025 – April 2026 (10 months) Central Bank of the Russian Federation | Moscow, Russia | www.cbr.ru Financial Sector – Banking Tech Lead, Development Team Led a development team of 8 people (developers, testers, analysts, technical writers). Key achievements: Launched a critical feature 2 months ahead of schedule (planned: 1.5 years) by reprioritizing and removing blockers. Reduced bug-fix time in testing from 1 week to 2–3 hours by migrating services to centralized CI/CD pipelines. Achieved full import substitution for all product components. Implemented a local solution in the absence of a centralized service, resulting in significant project budget savings and faster feature delivery. My team received the corporate award "Team of the Year" (2025) . Responsibilities: Backlog and sprint management, workload distribution. Service architecture design. Hiring, onboarding, motivation, and retention of developers. December 2023 – June 2025 (1 year 7 months) Central Bank of the Russian Federation | Yekaterinburg, Russia | www.cbr.ru Financial Sector – Banking Analyst (Data) – Internal Integration Service Development Enhanced an internal integration service for ingesting data from external sources. Key achievements: Established a prioritization process for unplanned enhancements, reducing chaotic team workload by 30% . Achieved 100% on-time release compliance for all service enhancements. Managed the full documentation lifecycle (TORs, architectural regulations, user guides) – up to 10 documents per project. Responsibilities: Analysis of enhancements. Updating documentation. Resource and effort estimation and justification. Central Bank of the Russian Federation (Previous role) Yekaterinburg, Russia | www.cbr.ru Financial Sector – Banking Data Analyst Focused on BI development (Tableau, Apache Superset) and automation of big data processing (SQL, Python). Key achievements: Reduced data preparation time for top management from several weeks to a few minutes by implementing interactive dashboards in Tableau/Superset. Implemented automated data quality controls, eliminating manual curator errors and freeing them from routine tasks. Initiated and secured management approval for changes to regulatory documentation, formalizing new reporting forms to improve analytics quality. Developed scripts for data enrichment and automated stress-test calculations. Awards: "Breakthrough of the Year" (2022), "Mega-Employee" (2021, 2022) – twice. Responsibilities: Reporting automation and visualization. Data quality control. Sberbank | Yekaterinburg, Russia | www.sbrf.ru Financial Sector – Banking Data Analyst Tasks: Forecasting and analyzing the bank's operating expenses. Allocating expenses to bank divisions. Developing a machine learning model for operating expense forecasting (Python/SQL). Results: Automated expense allocation calculations using VBA and Python, significantly reducing the division's routine reporting workload and improving data quality by eliminating human error. Developed a pilot ML model for forecasting the bank's operating expenses. (Previous role at Sberbank) Financial Sector – Banking Data Analyst Tasks: Information gathering and financial assessment of issuers, counterparty banks, management and insurance companies. Calculating limits and reserves for investments in securities, mutual funds, interbank loans, and derivative financial instruments (in line with Central Bank regulations 611-P, 590-P, 511-P, IFRS 9), and monitoring mandatory ratios. Assessing the bank's market risks (based on Basel III methodologies). Developing and updating methodologies in line with IFRS and Central Bank requirements. Designing reports and automating regular reporting (VBA, SQL). Results: Optimized risk limit and mandatory ratio calculations, reducing reporting preparation time from several hours to a few minutes. Developed and implemented new calculation methodologies and algorithms for reserves, enabling a successful transition to new regulatory documentation and reducing the bank's reserve requirements. Received the corporate "Bronze Badge" award in 2019.

Master's Degree (2014) Ural Federal University named after the first President of Russia B.N. Yeltsin, Yekaterinburg Institute of Physics and Technology – Applied Mathematics and Physics

Statistical Analysis, Mathematical Statistics, Mathematical Analysis Data Analysis, Exploratory Data Analysis (EDA), Data Interpretation Data Visualization (Tableau, Apache Superset) SQL, ClickHouse, Big Data, PySpark, Hadoop Python (pandas, NumPy, Jupyter Notebook) VBA, MS Excel Apache Airflow Requirements Analysis, Reporting Automation Agile Methodologies Personnel Management, Team Organization, Staff Training & Control Financial Metrics, Risk Assessment

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Russian: Native

English: B2 – Upper-Intermediate