Experience

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  Institute of mathematics and mechanics, spbu

  Apr 2012 - Jun 2013

  Assistant researcher

  Worked on parametric speech synthesis system for Russian language. Implemented program in Matlab which generates speech signal with given pitch energy and duration characteristics. Created UI for philologists experiments. Results were presented on several conferences in Russia and Europe. Coauthored a paper based on the work

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  Siemens

  Aug 2012 - Dec 2012

  Intern

  Implemented data analysis algorithms in Matlab: preprocessing, gap filling (SSA), forecasting (SSA,neural networks), spectral analysis (SSA, FFT, MUSIC, EV). Algorithms were used for anomaly detection and time series forecasting

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  Auditech

  Sept 2012 - Jul 2013

  Scientific researcher

  Implemented program in Matlab which removes non-stationary noises from speech databases (filtering, robust statistics). Participated in improvement of speech recognition system. Other projects related to speech processing

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  Ok.ru

  Jul 2013 - Nov 2015

  Data scientist

  Worked on Music service and Recommendations. Implemented audio fingerprinting system which allowed to delete music tracks at the request of copyright holders and reduced size of the music search index. Worked on the feed recommendations system. All the problems were associated with processing of large data sets and highly loaded services.Used technologies: Java, Hadoop, Pig, SQL, NoSQL

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  Epam systems

  Feb 2016 - Jan 2019

  Lead big data engineer

  Various outsourcing projects and POCs related to Big Data and data science for European and US companies. Among them: music recommendations system on Spark, image classification using convolutional neural networks on AWS services, chatbot POC using IBM Watson services, POC for test data generation using neural networks, Data Lakes building, implementation of ETL processes. Performed technical leadership of multiple projects.Duties: requirements clarification, design and documentation of technical solution, receiving approval from a customer, delegation of tasks inside the team, monitoring of tasks fulfillment, code reviews, mentoring of new team member, implementation itself.Used technologies: Java, Python, Scala, SQL, Hadoop, Hive/Impala, Spark, AWS/GCP Show less

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  Ipme ras

  Jul 2018 - now

  Senior researcher

  See Google Scholar for the list of published papers and conferences

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  Arrival

  Jan 2019 - Apr 2019

  Lead scala developer

  Worked on Operating System for robot manufacture. The system consisted of Storage (Blackboardpattern), declarative language (with it’s parser and executor) and APIs for external teams. Everythingwas written in Scala (Akka)

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  Assaia – the apron ai

  Apr 2019 - Dec 2020

  Lead data scientist

  Assaia provides Artificial Intelligence solution that watches aircrafts turnarounds in real time in order to understand what is happening and offers predictive analysis to better manage operations. - Worked on end-to-end solutions starting with machine learning / computer vision research andending with models productionalizing- Was responsible for core machine learning components including data preparation, sampling and deep learning models training for base events - Among solved tasks are images sampling/deduplication, training of generalized neural networks, passengers onboarding/offboarding detection using video data, segmenting deep neural network for detection of plane areas, people detection and several small tasks related to compute visionUsed technologies: Python, Tensorflow/Keras Show less

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  Hyprr

  Dec 2020 - Sept 2022

  Data science team lead

  Responsible for all machine learning related projects starting from architecture design and prototyping and finishing with models productionalizing and integration with other teams. Among projects currently working on are explicit (NSFW) content detection and Recommender Systems. Used technologies: Scala, Python, Apache Spark (Batch, Streaming, MLLib),Apache Kafka, Apache Cassandra

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  Sxope

  Oct 2022 - now

  Machine learning team lead

  Leading a team of 15+ engineers working on machine learning applications in the medical domain. The team is divided into four sub teams with their technical leaders.Projects are under NDA, but they revolve around two main areas: prediction of future diseases using tabular data and analysis of medical texts. Responsible for hiring a team, architecture and business reports design, integration of machine learning services and code reviews. Built interaction processes within the team and with other teams. Was also responsible for gathering business requirements and making presentations for the business before dedicated people for this role were hiredUsed technologies are Google Cloud Platform (BigQuery, PubSub, Cloud Composer, GKE) and standard Python stack with Pytorch for deep learning tasks Show less