Stanislav Khrapov Email & Phone Number

Frankfurt, He, De

Hamburg, Germany

- Developed failure detection system for installation process of industrial machines.- Replaced existing neural network model with substantially simpler, faster and more performantclassification algorithms allowing for greater explainability and faster experimentation cycle.- Increased transparency and clarity of communication with key stakeholders by introducing regularreview meetings, written reports, and newsletters.- Refactored existing POC level code of several microservices to production level using foundationalprinciples of software engineering.

Frankfurt Am Main, Hesse, Germany

- Developed trade surveillance system based on unsupervised time series classification machine learning models. Built realistic exchange market simulation with heterogeneous traders. Wrote and open sources fast Python-based order book matching engine (https://github.com/chintai-platform/OrderBookMatchingEngine). Designed a fully automated and reproducible pipeline to simulate market data, train and evaluate ML models catching illegal and anomalous trading behaviour.- Built a GitHub actions based CI/CD pipelines to release Node.js web applications interacting with the blockchain, check code quality, run unit and integration tests, search for code vulnerabilities, deploy to Kubernetes cluster running in the cloud. Organized processes across the company to streamline and speed up development and release activities starting from a PR and finishing with deployment to the production environment.- Implemented Infrastructure as a Code management of GitHub assets using Pulumi.- Participated in building TypeScript testing framework for Blockchain smart contacts.- Mentored junior data science colleagues. Organized technical workshop with a purpose of active exchange of ideas and latest developments in IT.

Frankfurt Am Main Area, Germany

- Designed and implemented custom time series models for forecasting of market freight prices and volumes, company internal financial indicators (EBIT, revenue, receivables, payables, etc.) to facilitate data-driven pricing decisions and liquidity planning.- Designed and implemented recommendation system to digitize and automate ground trasportation auctions in the carrier-dispatcher communication platform.- End-to-end ML cycle including data ingestion, processing, training, forecasting, evaluation, monitoring, orchestration, and delivery software.- Wrote software packages for automated model evaluation, comparison, and reporting.- Produced sophisticated static (Matplotlib, Seaborn) and dynamic (Dash, Bokeh) visualizations for presentation to internal business clients.- Worked in agile environment as a lead data scientist, scrum master, and product owner. Coordinated work of data scientists, data engineers, DevOps, business consultants. Mentored trainees and junior team members.- Designed and performed comprehensive company-wide workshops and multi-day trainings on machine learning for audiences of up to 150 people across diverse departments, both online and offline, with topics ranging from basics up to advanced hands-on instruction.

Moscow, Russian Federation

Research: Conducted research independently as well as with co-authors in the fields of financial econometrics, option pricing, volatility modelling​.Searched and surveyed all relevant literature on the subject. Collected, cleaned, and analyzed complex data from such sources as OptionMetrics, CRSP, TAQ, Compustat, Quandl. Collected unstructured data using web parsing methods and regular expressions.Performed Monte Carlo experiments for model selection purposes.Advanced knowledge of parametric and non-parametric estimation methods of non-linear models including MLE, GMM.Implemented several models and estimation methods as Python modules publicly available from GitHub repository.Presented at major international economics, finance, and econometrics conferences.Teaching: Intermediate Econometrics, Advanced Econometrics, Financial Econometrics, Data Analysis in Python​. 10-50 students in each class.Supervision: 4-8 master and bachelor students each year.

Chapel Hill, Nc

Teaching: Recitations in graduate classes: Intro to Probability Theory, Applied Econometrics, Advanced Econometrics.

Cary, Nc

May - Aug 2007, 2008, 2009, 2010- Programmed C module for estimation of GEE type models.- Wrote examples of usage of new Copula procedure- Participated in writing of future publication “SAS/ETS User’s Guide” by drafting chapters on time series models- Added examples of usage and edited manuals for SAS/ETS procedures- Programmed GUI in JMP for analysis of limited dependent variables

New York, Ny

Improved annual statistical report on contributions and expendituresof member countries by implementing multi-year perspective

Novosibirsk, Russian Federation

Analyzed current statistics, reviewed recent publications

Phd, Economics, Financial Econometrics

Thesis - "Essays in Asset Pricing"

Ma, Economics, Econometrics

Thesis - "Censored Regression Models: An Empirical Investigation of Charitable Donations"

Ma, Economics, Mathematical Modeling

Thesis - “Dynamic model of population and production”

Ba, Economics, Mathematical Modeling

Thesis - “Relation marketing with the use of database”