Kostya Timchenko

AI Researcher

San Francisco, California, United States11 yrs 4 mos experience

Key Highlights

Ph.D. in Mathematics with machine learning expertise.
Developed innovative fraud detection and NLP models.
Strong analytical skills with a focus on customer outcomes.

Stackforce AI infers this person is a Machine Learning Engineer with a strong background in Data Science and Mathematical Analysis.

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Skills

Other Skills

Algebraic GeometryAmazon Web Services (AWS)Analytical SkillsData AnalysisData ScienceDeep LearningMachine LearningPandas (Software)Problem SolvingPyTorchPython (Programming Language)SQL

About

Software engineer with a passion for understanding the ‘why’ of the problem and the impact of solutions on customer outcomes. Experienced in applying machine learning to solve product needs. Ph.D in Mathematics.

Experience

Stripe

Machine Learning Engineer

Jul 2025 – Present · 8 mos · San Francisco, California, United States

Ocrolus

2 roles

Software Engineer

Jan 2023 – Oct 2023 · 9 mos · New York, United States

Developed and expanded document fraud detection offerings
Researched and developed new tools for pdf forensic analysis

Data Scientist

Jan 2021 – Jan 2023 · 2 yrs · New York, United States

Built and deployed volume forecast models to enable the operations team to make high-quality head-count decisions
Developed an NLP model to predict industry classification of small businesses using business names and transactional data with high accuracy
Developed and productionalized 40 new cash flow metrics in the Ocrolus’ API
Collaborated with product and client success teams to improve the transaction classification product based on customer feedback

University of notre dame

2 roles

Research Assistant Professor

Aug 2020 – Jan 2021 · 5 mos · Notre Dame, Indiana, United States

PhD Researcher

Aug 2014 – Aug 2020 · 6 yrs · Notre Dame, Indiana, United States

Taught multiple calculus courses to over 60 undergraduates, preparing lecture notes and grading tests
Presented independent research at various institutions, adapting to different audiences (general
public, undergraduates, graduates, and researchers)
Organized weekly seminars for the department
Mentored undergraduate researchers on their independent projects in mathematics