Dimitri Kupov

About Dimitri Kupov

Experienced, detail-oriented Data Engineer, Analyst and Data Scientist, with extensive background in high volume, mission-critical, real-time transaction data preparation and visualization. I perceive math, data analytics and creativity in machine learning as my intrinsic value, my “eigenvalue”, if I may say so. Passionate with quantified methods & values-adding analytics | Reasonably creative | Devoted to imply new meanings and make everyone\'s work meaningful in an agile team with 10+ years Project Management experience.I am passionate to deploy mathematical methods to analyze, lead, and predict clients behavior and activities. I do my best to treat the values of my colleagues and clients as my personal priority.My skills stand on active listening | affiliative questioning | combinatorial analysis | storytelling based on data visualization and appropriate emotional response | adaptable | engaging and decisive actions. Accomplishments.Automated month end closing procedures cutting closing time in half. Worked with business units\' leaders to budget and forecast expenses and revenues.Developed a system to pull raw data from legacy data base and Oracle to compile it into a new system to comply with external auditor’s recommendations.Developed smart automated system of forensic accounting analysis committed against the company.Led and motivated agile teams that created an extraordinary community that is helping each member of the team to achieve the highest potential, performance and enjoy the working environment. Developed a model to analyze and predict judicial outcomes related to a meaningful intellectual property.

Experience

1. Sr Data Analyst, Cloud Data Engineer Architect

   Burns & McDonnell

   Jan 2023 — Present · Newton, MA, US

   Mapped end-to-end Data Pipelines that caused rapidly changing dimensions on Azure and Databricks with T-SQL, Python, scaling performance with Spark framework; automated analytics with MLflow to make it ready for serve self-service reporting objects on Power BI, Tableau.• Proposed IP-driven AutoML solution for data engineering (a.k.a. liquid clustering) & ML-driven data products development that converts data models from Opex to Capex. • Designed on Github specs that automate, control, & streamline project behavior in different environments deploying Databricks bundle (tweak configs) solution. • Designed LLM-embedding environment on Databricks with options to verify Contingency requirements and USGAAP principles to relational datasets that triggers ‘flags’ on Projects for auditors & provides precise answers to PMs on a specific industry, or safety/finance-related questions through the automated chat.

Education

• Moscow State Institute of International Relations (University) MFA Russia MGIMO

  Master's degree, MS in Applied, Computational Mathematics & Economics

• Hult Ashridge Executive Education

  Master of Business Administration - MBA, Managerial Finance, Project Management, Data Analysis

• Massachusetts Institute of Technology

  Postgraduate Degree, Data Science, Data Modeling