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Senior Manager, Forecasting Research at Amazon | Kaggle Grandmaster | Time-Series Foundation Models & Applied ML
Machine learning engineering leader with 15+ years of experience in solving different data science problems and building superior machine learning pipelines. Unique combination of excellent knowledge of theoretical aspects, outstanding intuition, strategical vision and expertise in industrial machine learning with proven records of launching models in production resulted in significant business impact. Deep understanding of machine learning techniques for structured and unstructured data including deep learning algorithms, unsupervised techniques, recommender systems and generative methods; excellent knowledge of cloud systems, distributed computations on CPU/GPU and big data.
Lomonosov Moscow State University (MSU)
PhD, Mathematics
September 1, 1999 – January 1, 2008
Amazon
Senior Manager, Applied Science, Forecasting at Amazon Supply Chain
March 1, 2026 – Present
New York, United States
Amazon
Senior Manager, Research Science (Demand Forecasting)
September 1, 2021 – March 1, 2026
New York, United States
American Express
Head of Machine Learning Centre of Excellence (VP)
October 1, 2019 – September 1, 2021
American Express
Machine Learning Engineering Manager (Director)
August 1, 2018 – October 1, 2019
American Express
Staff Machine Learning Engineer
February 1, 2017 – July 1, 2018
Freelance
Kaggle Grandmaster
December 1, 2016 – Present
American University of Sharjah
Assistant Professor
September 1, 2012 – February 1, 2017
Sharjah, UAE
Lomonosov Moscow State University (MSU)
Assistant Professor
September 1, 2007 – August 1, 2012
Quantum computing
Coursera
June 24, 2026 – Present
American Express & Harvard Certificate in Leadership Excellence
Harvard Business Publishing
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience in large, data-driven organizations like Amazon and American Express, coupled with a strong academic background and competitive ML achievements, suggests a good cultural fit for a demanding, innovation-focused environment. The diversity of projects (forecasting, fraud, credit risk) and leadership roles indicates adaptability and a broad skill set. However, the target role of 'Data Analyst' seems significantly under-leveled for this candidate's extensive experience and leadership profile, which might indicate a mismatch in expectations or a potential overqualification for a pure analyst role. The candidate's profile is more aligned with a Lead Data Scientist, Principal Applied Scientist, or ML Engineering Manager role.
Soft Skills & Operational Fit
The candidate's resume highlights strong leadership, team management, and mentoring skills. Experience in defining long-term vision, talent strategy, and collaborating with engineering and analytics teams suggests excellent operational fit for senior roles. The description of driving modernization and aligning MLOps infrastructure indicates a proactive and strategic approach to operational challenges. The Kaggle Grandmaster status also implies strong problem-solving and analytical thinking.