Natalia Tsarkova

- Development/maintenance of Kubeflow and Airflow pipelines. Building Docker images, configuring CI/CD within Gitlab repositories, creating Grafana alerts & monitoring - Creation of end-to-end DS&ML solutions: business requirements, model & ML pipeline development, deployment in production, configuring retraining Key achievements: - Significantly improved RLTV pipeline, reducing model RMSE by 30% - Developed Python library for quicker deployment to Kubeflow, reduced the average time of deployment by 50%

Key responsibilities: - Quality control of ML models used in different departments: binary and multiclass classification, regression, time series, clustering, text mining - Creation of alternative models with higher quality and performance Key achievements: - Developed a Python library for automatic modelling which reduced the average time of model quality check by 40% - Created a validation methodology for clustering and time series model

As an expert of client analytics and reporting department I was working with big data sets using various software (R, KNIME, SQL) and applications of machine learning, including - design of segmentation and predictive models of client behavior using machine learning methods - development of a set of covariates to be used in models’ construction and development of forecasting models - model deployment into production using KNIME software

During my work in LPV, the biggest Russian loyality program managing company, I analyzed data using SQL, SPSS Modeler, R and MS Excel: - preparation of different forecasts - estimation of effectiveness of marketing campaigns and providing recommendations to achieve best results - data base analysis and suggesting improvements to maximize effectiveness of marketing activities - performing analytical and statistical reporting on request

Took part in an international research traineeship at Novancia Business School Paris, France. Analyzed various data using different methods of statistical analysis, for example: - statistical hypothesis testing, correlation and regression analysis - regression models: linear, logistic, ordinal regression, etc. - cluster analysis

Master of Science in Business Informatics, National Research University Higher School of Economics (HSE) Moscow, Russia. Master’s program Big Data Systems. GPA: 8 / 10 | Thesis: Machine learning applications to genome annotation problem

Master of Science in Engineering, UAS Technikum Wien, Vienna, Austria. Erasmus double degree Master’s program Information Systems Management.

GPA: 4.95 / 5 | Degree with honors, specialization in Mathematical Methods in Economics Thesis: Economic and mathematic research of the level of labor market tension in Russian Federation regions