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Senior Analytics Engineer

EPAM Systems

• Pharmaceuticals - Data Science & Analytics Team: Contributed as a Business Intelligence Engineer to the Market & Sales Analytics branch of a leading pharma enterprise. Supported sales strategy development by creating Tableau dashboards for internal management, integrating data from Snowflake.

• Financial Services - Capital Market Data Migration: As an Enterprise Architect, was responsible for the migration of capital market data from an on-premise MS SQL Server to Google Cloud Platform. Created comprehensive data mappings, object dependencies, and reconciliation of data usage in BigQuery.

• Insurance - Data Architecture Redesign: Engaged as a Data Engineer to overhaul the data architecture of a segment of the client's website. Conducted extensive Data Discovery, mapping table contents, interrelations, and scheduled processes in MS SQL Server.

Business Intelligence Analyst, Data & Analytics

Experian

• Trusso Deployment (EMEA, UK, APAC): Played a pivotal role in implementing Experian's transaction categorization engine, Trusso, across various regions as part of the Open Banking initiative. As a Data Engineer with Python, I contributed to the development of the data pipelines for the ML models used. Focused on standardizing client delivery, enhancing data onboarding processes, and providing technical support for new market deployments. Additionally, contributed to operational documentation and comprehensive internal tutorials in the Confluence project space.

• Application and Behavioral Scorecard Development: Involved in data engineering for the creation of scorecards tailored for EMEA banks, improving accuracy in credit risk assessment.

• Machine Learning in Credit Risk Modeling: Developed an automated machine learning tool using SAS Macros for XGBoost/RandomForest modeling, enhancing credit risk analysis capabilities.

• Big Data ETL Optimizations for the UK Banking Sector: Engineered significant process improvements using PySpark, Spark SQL, and Python on RDDs in Apache Spark, leading to substantial reductions in processing time for Market & Portfolio Insight.

• Credit Risk Reporting: Utilized R for credit risk reporting, supporting strategic decision-making.

• IFRS 9 Data Engineering for Bank Norwegian: Specialized in data engineering for IFRS 9 credit risk models, focusing on Loss Given Default (LGD) calculations and SQL optimizations.

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Borislava Goneva's Linkedin Analytics

Borislava Goneva

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Borislava Goneva

Want to drive more opportunities from LinkedIn?

Borislava Goneva's Linkedin Analytics