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Роман

Аналітик

City of residence:
Chernivtsi
Ready to work:
Remote

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ROMAN BEZRUCHKO
DATA ANALYST | SQL • PYTHON • EXCEL • POWER BI | DATA QUALITY & OPERATIONS
Kharkiv, Ukraine | [open contact info](look above in the "contact info" section) | [open contact info](look above in the "contact info" section)
PROFESSIONAL SUMMARY
Data Analyst with 4+ years in fintech and technical support, experienced in large-scale data analysis, SQL optimization, data
validation, incident investigation, and stakeholder support. Strong hands-on background with SQL Server/T-SQL, Python (pandas,
NumPy, matplotlib), Excel, Power BI, MongoDB, and multi-source data. Proven track record of improving report performance,
automating operational workflows, identifying root causes of data issues, and translating analysis into actionable business insights.
Comfortable working autonomously with distributed teams in dynamic, data-sensitive environments.
CORE SKILLS
SQL & Data: SQL Server, T-SQL, stored procedures, CTEs, window Python & Excel: Python (pandas, NumPy, matplotlib), EDA, anomaly
functions, indexing, execution plans, MongoDB, BigQuery detection, automation, APIs/JSON; Excel/Google Sheets
Data Quality & Operations: Data validation, reconciliation, root cause Analytics & BI: Hypothesis validation, A/B testing, KPI analysis, Power
analysis, incident investigation, alerts, operational support BI (DAX, Power Query, RLS), Tableau, Looker Studio
Engineering & Workflow: ETL/ELT, dbt, Power BI Dataflows, Azure Collaboration: Stakeholder communication, client/internal requests,
Data Factory basics, Airflow basics, Git, code review cross-functional collaboration, autonomous remote work

PROFESSIONAL EXPERIENCE
Data Analyst | Finance Space Crew (formerly MyCredit), Kharkiv | Mar 2022 - Present
• Analyze and model multi-source datasets from SQL Server, MongoDB, Google Sheets, and Python/pandas, reducing manual data
preparation by 30%.
• Write, optimize, and maintain T-SQL queries and stored procedures; execution-plan analysis, indexing, CTEs, and window
functions improved half-hourly report performance by 30% and reduced CPU usage by 50%.
• Investigate data inconsistencies and production/reporting issues, perform validation and root cause analysis, and resolve critical
defects; fixed 20+ critical issues and reduced SLI-related incidents by 80%.
• Build data-quality checks, reconciliations, and monitoring logic to ensure reliable metrics and support day-to-day operational
decisions.
• Validate business and product hypotheses using A/B testing and statistical analysis, turning findings into actionable
recommendations for stakeholders.
• Developed 10+ stakeholder-facing Power BI dashboards using DAX, Power Query, and RLS; collaborate with Finance, Risk,
Product, and other teams on data requests and issue resolution.
Support Engineer | Finance Space Crew, Kharkiv | Jan 2020 - Mar 2022
• Monitored ETL jobs and system performance, investigated operational failures and bottlenecks, and helped improve batch
throughput by 80%.
• Built data validation rules and alerts that reduced data defects entering reporting by 50%.
• Handled internal stakeholder data requests and automated recurring Finance/Risk extracts with SQL and Power BI Dataflows,
reducing turnaround from 2 hours to 10 minutes.
• Worked in a fast-paced support environment requiring independent troubleshooting, prioritization, clear communication, and
reliable handling of sensitive business data.
SELECTED TECHNICAL EXPERTISE
SQL: SQL Server, T-SQL, stored procedures, indexing, execution plans, CTEs, window functions | Python: pandas, NumPy,
matplotlib, EDA, workflow automation, APIs/JSON | BI: Power BI, DAX, Power Query, RLS, Tableau, Looker Studio | Data stack:
MongoDB, BigQuery, dbt, ETL/ELT, Azure Data Factory basics, Airflow basics, Git
EDUCATION & TRAINING
KNURE - Kharkiv National University of Radioelectronics | Specialist, Information Technology and Management | 2016 - 2020
KCTC - Kharkiv Computer and Technology College | Junior Specialist, Computer Science | 2012 - 2016
Google / Coursera | Foundations: Data, Data, Everywhere | 2024
Mate Academy | Data Analytics coursework - SQL, Python, Excel, visualization, statistics, machine learning
LANGUAGES
Ukrainian | English

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