Savelii Seliaev

I’m an MSc graduate in Applied Data Analysis with a strong quantitative background in applied mathematics, statistics, machine learning, and data analytics. My academic focus included Data Analytics, Machine Learning, Biostatistics, and Data Engineering, where I developed both technical and analytical problem-solving skills.

I’m particularly interested in the intersection of data, AI, and business decision-making. What motivates me most is transforming raw information into structured insights, KPIs, dashboards, and practical recommendations that help organizations improve processes and make better decisions. I enjoy connecting technical analysis with business needs and presenting findings in a clear and understandable way.

To strengthen my practical experience, I built several end-to-end analytics projects using Python, SQL, and Power BI. In my Credit Risk Reporting Dashboard project, I designed a SQL data model with 30k+ records, developed KPIs such as default rate and exposure, and created dashboards for portfolio monitoring and risk analysis. In a separate Bank Marketing Analytics project, I analyzed customer campaign behavior, identified high-value customer segments, and translated findings into business-oriented visualizations and recommendations.

I adapt quickly to new tools and technologies and enjoy learning about AI, automation, business intelligence, and process optimization. I’m currently looking for opportunities where I can grow as a data, business, or AI-oriented analyst while contributing with analytical thinking, structured communication, and a strong willingness to learn.