Communication Skills / Presentations / Storytelling
Quantitative Analytics skills
Market Research and Monitoring
Tech skills and habits:
Current
Python (+numpy+scipy+matplotlib+...)
Tensorflow
MapReduce
Linux/BSD user
Past
ASM: x86, ARM7, Z80
C & C++
Perl & PHP
PostgreSQL, MySQL,
HTML+JS
D3+Processing
Professional background:
Yandex Germany (2010-2022)
Position: Senior Data Analyst
Key responsibilities:
To provide a full cycle analytical support, including:
To formulate KPIs and metrics of the product
To measure dynamics of metrics changes (i.e., using AB-testing tools)
To check statistical significance of hypotheses
To interpret results of the research
Corelogic (2005-2010) Consulting and IT solutions for the financial sector
Position: CTO, cofounder
Key responsibilities: Lead analyst and system architect, project manager. Head of development team
Computer Science department, MSU (2002-2005) Laboratory of Computer Systems
Position: Developer, consultant, postgraduate
Key responsibilities: Postgraduate research and development, teaching computer science.
Significant projects:
The environment for the visualization and analysis of the functioning of distributed software and hardware systems.
Participation in a project aimed to create a precise simulator of the embedded software with ability to switch between simulating hardware and using the real one.
Consulting the team working on the distributed network security systems.
AlphaSquare (1999-2002) Web studio
Position: Developer, later lead developer
Key responsibilities: Developer, System architect
Significant projects:
Designing the architecture, developing and deploying 20+ web sites and portals
Reverse-engineering of an implicit model of search engine’s ranking mechanism on the basis of publically available information
Building early analogues of today’s common web technologies (AJAX, JSON) based on functionality of IE4, NN4
Method and device for creating contents recommendations in recommendations systemUS20180011937A1, EP3267386A1, RU2632132C1
There is disclosed a computer-implemented method of generating a content recommendation for a user of an electronic device, the method executable by a recommendation, the content recommendation being associated with a content item available at one of a plurality of network resources accessible via the communication network. The method comprises: executing a first machine learning algorithm module in order to determine a sub-set of recommended content sources from a plurality of possible content sources that is based on at least some of a first sub-set of user-specific content sources and a generated second sub-set of user-non-specific content sources; analyzing the sub-set of recommended content sources to select a plurality of potentially-recommendable content items; executing a second machine learning algorithm module in order to select, from the plurality of potentially-recommendable content items, at least one recommended content item; the selection being made on the basis of a user-profile-vector.
Method of and system for parameter-free discovery and recommendation of areas-of-interestUS20170024397A1, RU2015125820A
A method and system for processing a user request for a recommended area of interest includes the steps of receiving the request including an indication of an electronic device geo-location and a user defined search constraint; receiving data associated with photographs associated with geo-objects, the data comprising geo-location coordinates of the photographs, the geo-location coordinates of the photographs being in proximity with the device geo-location; computing a plurality of region representations based on the geo-location coordinates of the photographs, each region representation being associated with a unique photograph density calculation parameter, the computing comprises determining a potential area of interest in each region representation, each region representation being a candidate for an optimal region representation; determining the optimal region representation based on the user defined search constraint; and displaying to the user the recommended area of interest that corresponds to the potential area of interest of the optimal region representation.
Education:
MSU (1997 – 2002)Computational Mathematics and Cybernetics
Degree: Master of Science in Math and Computer Science
Diploma title: 'Development of the environment for the visualization of functioning distributed programs'
Nominal grant from the company Sun Microsystems for “Development of the internet operable control device for home appliances” (in conjunction with Einthoven University, the Netherlands)
Coursera courses
Computer Networks, 96.7% (University of Washington, 2013)
Computational Molecular Evolution, 99.7% (Technical University of Denmark, 2013)
Networked Life, 97.18% (University of Pennsylvania, 2012)
Social Network Analysis, 94% (University of Michigan, 2012)
Gamification, 98.75% (University of Pennsylvania, 2012)
Natural Language Processing, 94.9% (Stanford, 2012)
Model Thinking, 'above 90%' (University of Michigan, 2012)