Experience

Mar 2023 – now, Aachen, Germany
CV Entry: Machine translation model development and enhancement for various language pairs. Research on meta-data extraction and applications, gender/formality disambiguation, data enrichment and processing with fine-tuned LLMs.
Actually: NDA / TBA

Oct 2022 – Feb 2023, Aachen, Germany
CV Entry: Model enhancements to the Alexa end-to-end speech recognition pipeline, including forced alignment models rollout. Made advancements for the German locale release, which enabled reaching the yearly accuracy goal.
Actually: a short leap into ASR, acoustic modeling, Amazon infrastructure. Caught a layoff together with other colleagues on probation period.

Jun 2021 – Oct 2022, Moscow, Russia
CV Entry: ML-based forecast for Meteum.AI. Development of deep learning models for the precipitation and cloudiness forecast based on satellite images and other data. Designed, implemented and rolled out a novel accurate cloudiness prediction model. Advanced the satellite-based precipitation model with a successful rollout to North/South America and Asia.
Actually: ML tasks related to weather forecasting. Worked on a diverse set of dirty geo/satellite/user/user/forecast data.

Jun 2020 – Jun 2021, Moscow, Russia
CV Entry: Enhancement of the existing face recognition pipeline in the Industry Video Application Lab of Huawei Moscow Research Center. Research on feature representations and uncertainty estimation.
Actually: Top-tier (definitely within global top-10) scientific/engineering face recognition team aimed to excellent performance on the hardware.

Sep 2016 – Nov 2020, Moscow, Russia
CV Entry: Research on the application of machine learning to elastic strain engineering for semiconductors. Designed and implemented deep NN-based surrogate models for quantum-mechanical simulations of strained crystals; results are patented. Visiting researcher at MIT (Nov – Dec 2017, Aug – Sep 2018). Data analysis and predictive model development in joint projects with industrial companies.
Actually: a PhD-related entry: travelling to MIT for research, collaborating with theoretical physicists, etc — see more details on Research. During this time, I was also secretly working part-time outside of academia, see Project Experience below.

Aug 2015 – Oct 2017, Moscow, Russia
CV Entry: Data engineering, including ETL procedures, near-real-time scripts on Hive and Spark, marketing tracking system pipelines. Developed and implemented original revenue and churn prediction systems based on ML algorithms. Interactive visualizations for HQ, game balancing, ad-hoc and A/B testing analytics, cluster analysis. Head of summer DS internship.
Actually: my first ML/DA job. Tons of experience, mistakes, and growth. Entered as a Data Analyst and left to pursue PhD.

Jun 2012 – Aug 2014, Moscow, Russia
CV Entry: Research on numerical methods for various problems of mathematical physics. Numerical experiments, academic writing.
Actually: a part-time academic job that gently (not really) introduced me to the world of science I fell in love with.

Jun 2019 – Jun 2020
CV Entry: Data management for the Functional Neurophysiology lab. Exploratory analysis and visualization, development of state detection systems based on EEG, EMG, RESP and other sources. Hypothesis check for psychological and physiological experiments.
Actually: definitely the most crazy and interesting experience I had. We were measuring people under hypoxia, on balance boards, during archering, playing VR games, on ski, on carts, etc etc

Aug 2018 – Feb 2020
TL;DR: Developing news analytical and clustering systems with a Telegram interface (ONOScope). Designing and implementing the workflow for accidents detection, with a voice-assistant app as a result. Sentiment and clustering analysis for clients.
Actually: a solid NLP experience on the rolling data back to the time when there were no Transformers and some free news still existed in Russia.

Dec 2018 – Sep 2019
CV Entry: Analyzing and interpreting the log files from algorithmic trading stock systems. Taking part in implementing an ML-based (using NLP-like methods) clustering and warning system for users. Supervising junior colleagues
Actually: DS consulting on a really specific data. First time I got paid for the clustering algorithm.

Aug 2017 – Feb 2018
CV Entry (hidden): Data journalism, match outcome prediction systems for DotA2 and CS:GO, including the development of the AI-based expert writer for betting service. Consulting and prototyping a system for churn and revenue prediction.
Actually: I thought I love DotA so much but wasn’t a really useful guy for this startup’s success.

Sep 2014 – Apr 2016
CV Entry (hidden): Monitoring and analysis of university online communities. Instagram data extraction and exploration, including student profile clustering and geotags analysis. Developed near-real-time scripts and dashboards for university management. Also analysis of bioinformatics education in Russia during the HSE-EMC joint project grant “Analysis and visualization of scientific bioinformatics communities based on RISC and other open sources”. Results are published in Sk Biomed Almanac.
Actually: these early youngster projects which were paid from the random research grants. Thanks to them, I got used to the consulting lifestyle and got my first connections and future clients.