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Data Analyst

Russia, Moscow
Added: 09.04.2026
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Location:

Russia, Moscow

Birthday date:

10/12/2001

Experience level:

1-3 years

Education level:

Bachelor

Languages:

Russian: Native

English: B1

About

My career began in client-facing banking roles, where I developed deep empathy for customer needs and a strong understanding of financial products. Driven by curiosity, I upskilled in data technologies—mastering SQL, Python, and BI tools—and transitioned into a Data Analyst role. Today, I bridge business and technology: I build data pipelines, create interactive dashboards, and deliver insights that directly influence strategy. I’m now planning to relocate to Serbia and contribute my hybrid skillset to a collaborative, impact-focused team.

Work experience

Senior Customer Service Manager

PAO JSCB Avangard

2022-2025

End-to-End Client Service Management: Guided customers through the full service lifecycle, from initial needs assessment and product presentations to account/deposit onboarding and credit/debit card issuance.

Consultative Advisory & Financial Education: Provided expert guidance on banking products, matching solutions to individual financial goals while improving clients’ financial literacy and driving informed decision-making.

Operational Execution & Compliance: Processed account openings, deposit management, and card issuance with strict adherence to internal SOPs, KYC/AML regulations, and service quality standards.

Data Analyst

TechnoProgress, Research Center

2025

Strategic Leadership: Directed multiple business units, driving systematic development and ensuring achievement of key performance indicators (KPIs) across departments.

Data Integration & Governance: Systematically collected and consolidated data from internal registries, CRM systems, and external sources, ensuring data completeness, accuracy, and reliability for decision-making.

ETL Automation: Leveraged Power Query (Excel & Power BI) to automate end-to-end ETL processes — cleaning, transforming, and merging data from heterogeneous sources, eliminating manual intervention and reducing processing time.

Advanced Data Extraction: Developed complex SQL queries (PostgreSQL) for efficient data retrieval, filtering, and pre-processing, supporting analytics and reporting workflows.

Python Automation & Analysis: Built Python scripts (pandas, NumPy) for advanced data manipulation, automation of repetitive tasks, and large-scale array processing, improving operational efficiency.

BI Dashboard Development: Designed and deployed interactive Power BI dashboards and detailed reports, integrating pre-processed data from Power Query and Excel to visualize KPIs, track performance trends, and support strategic planning.

Customer Segmentation: Engineered dynamic customer segmentation models using a combination of SQL, Python, and Excel, enabling targeted outreach strategies for the sales team and improving conversion efficiency.

Feedback Analytics & Process Optimization: Maintained and analyzed sales team feedback registers; applied Python and Power BI to identify systemic issues, emerging trends, and data-driven recommendations for team performance optimization.

Education:

Moscow University named after S.Yu. Witte, Moscow

Faculty: Economics and Finance

Specialisation: Business analytics in economics and management

Graduation year: 2025

Key skills:

Technical Skills:

🔹 Programming & Scripting
Python: Data manipulation and analysis with pandas, NumPy; automation scripting
SQL: Advanced query writing (JOINs, window functions, CTEs); PostgreSQL, ClickHouse
VBA/Excel Macros: Automation of repetitive tasks, custom functions, dashboard interactivity
Scala: Working familiarity for big data processing contexts
🔹 Databases & Big Data
Relational DB: PostgreSQL (query optimization, schema design)
OLAP/Columnar: ClickHouse (high-performance analytics)
Big Data Ecosystem: Hadoop, Hive, Apache Kafka (stream processing fundamentals)
Data Engineering: ETL/ELT pipeline design, data modeling, workflow orchestration with Apache Airflow
🔹 BI, Analytics & Visualization
BI Tools: Power BI, Yandex DataLens (interactive dashboards, KPI tracking)
Excel: Advanced level — PivotTables, Power Query, complex formulas, data visualization, dashboarding
Statistics: Foundational knowledge of probability theory, descriptive/inferential statistics
🔹 DevOps & Infrastructure
Linux: Command line proficiency, basic system administration tasks
Containerization: Docker (container creation, basic orchestration concepts)
Version Control: Git (branching, merging, collaborative workflows)
🔹 AI & Automation
Prompt Engineering: Advanced techniques for solving applied business tasks with LLMs
LLM Automation: Creating templates, parsing unstructured data, text summarization, workflow automation