Andrei Kavalenka
@andreikavalenka
Data Scientist leveraging AI and analytics for complex business solutions.
What I'm looking for
I am a Data Scientist with over 5 years of commercial experience, specializing in leveraging AI and analytics to solve complex business challenges. My journey has been marked by a commitment to excellence in development, particularly in Python, where I have successfully built end-to-end machine learning projects capable of processing vast datasets.
At Talent Shark, I developed an LLM-powered tool for automated job-candidate matching, which significantly improved the precision of candidate selection. My role at BNY Mellon involved creating intelligent agents for data analysis, enhancing decision-making through advanced visualizations and statistical metrics. I am passionate about continuous improvement and have consistently achieved remarkable enhancements in model accuracy and performance through rigorous analysis and retraining.
Experience
Work history, roles, and key accomplishments
Data Scientist
BNY Mellon
May 2023 - Present (2 years 1 month)
Developed an intelligent agent as part of a multi-agent system for analyzing tabular data, generating over 5 types of visualizations and 10+ statistical metrics. Designed a retrieval-augmented generation (RAG) agent to extract and structure information from ~100 PDFs, enhancing search accuracy. Created forecasting models for business variables, mainly focusing on time series data, achieving up to
AI Engineer
Talent Shark
Dec 2024 - Present (6 months)
Developed an LLM-powered tool for automated job-candidate matching, enabling structured comparison across multiple criteria. Designed and implemented an LLM parser to extract key job requirements from vacancies and built a parallel LLM-based pipeline for candidate profile parsing. Implemented a weighted scoring system and ranking logic to shortlist top candidates, delivering structured summaries f
Machine Learning Engineer
DataMola
Mar 2022 - Jun 2023 (1 year 3 months)
Developed an end-to-end internet TV ratings prediction project using Python and Bash, boosting business metrics up to 40% and incorporating MLOps features. Improved model predictions by 50% through monthly retraining, error correction, and refining preprocessing/postprocessing pipelines. Constructed data pipelines on AWS S3 and designed a Bash pipeline for manipulating Python projects on AWS EC2,
Data Scientist
Innowise Group
May 2021 - Apr 2022 (11 months)
Applied various computer vision and custom methods to recognize italic and bold text with accuracies of 83% and 78% on customer's test dataset. Designed custom functionality to structure tables, paragraphs, and detect underlined/strike-through text in customer's PDF files, achieving 85-97% recognition accuracy. Linked C++ and Python using Ctypes and C++ libraries for parsing PDF structures, result
Education
Degrees, certifications, and relevant coursework
Belarusian State University of Informatics and Radioelectronics
Bachelor of Technology, Information Technology and Control
Studied Information Technology and Control, gaining foundational knowledge in various aspects of IT and system management. Focused on the principles and applications of technology and control systems.
Availability
Location
Authorized to work in
Job categories
Skills
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