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Technical Lead
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I optimise and automate things
National Technical University of Ukraine 'Kyiv Polytechnic Institute'
BS, Applied Mathematics
January 1, 2012 – January 1, 2017
MIADVG LLC
Technical Lead
September 1, 2020 – Present
Drafter AI: Marketing Content Generation
Co-Founder and CTO
March 1, 2020 – July 1, 2020
Phonal Technologies
Co-Founder and CTO
January 1, 2019 – September 1, 2020
DeckRobot
Lead Machine Learning Engineer
July 1, 2018 – January 1, 2019
VisaHQ
Machine Learning Engineer
December 1, 2017 – July 1, 2018
Ventseek Ltd
Machine Learning Consultant
September 1, 2017 – December 1, 2018
UvoCorp
Computational Linguistics Consultant
September 1, 2017 – December 1, 2017
Freelance
Machine Learning Consultant
June 1, 2017 – August 1, 2017
Self-Employed
Data Scientist
April 1, 2017 – September 1, 2017
KV Social
Computer Vision Engineer
October 1, 2016 – March 1, 2017
KV Social
Natural Language Processing Engineer
February 1, 2015 – September 1, 2016
KV Social
Machine Learning Engineer
July 1, 2014 – March 1, 2015
ReciproCoach
Machine Learning Engineer
January 1, 2014 – July 1, 2014
Net-Simple
Software Engineer
June 1, 2013 – January 1, 2014
Virtual Asistant
April 1, 2017 – Present
Virtual assistant with programmable fluent API to teach him perform external API calls. Used: - TF-IDF - Gradient Boosting - NLTK - Sklearn
RNN based conversational agent
November 1, 2016 – April 1, 2017
RNN based generative chat bot. Used: - tensorflow - Amazon ML AMI - RNN - LSTM - word2vec
Seat Belts Recognition
January 1, 2016 – May 1, 2016
System to detect if person using seat belts when riding a car. Used: - TensorFlow - AlexNet - VGGNet
Software Problems Detection using Support Tickets Clustering
September 1, 2015 – October 1, 2016
System to detect problems in software using feedback from users. It's helpful for systems with great user base and can make problems detection much quicker. Used: - python - c-means - DBSCAN - TF-IDF - Apache Spark (distribution in case huge amount of data coming in)
Sentiment Classification System
February 1, 2015 – June 1, 2015
NLP sentiment classifier for further analysis purposes Used: - python - XGBoost - Amazon ML AMI for computition - word2vec embedings - TF-IDF vectorization - Ensemble models (random forest, gradient boosting) - RNN
Human Gait Detection
January 1, 2014 – June 1, 2014
Detection of human using bio-metric data from accelerometer of mobile device. Used: - Time series analysis - Anomaly detection - Fourier decomposition - Dynamic time warping
Cultural Fit Analysis
The candidate has a strong background in various ML domains, including NLP, Computer Vision, and time series analysis, indicating adaptability and a broad technical interest. Their experience as a Co-Founder and CTO suggests an entrepreneurial mindset and a willingness to take ownership, which can be a strong cultural fit for innovative environments. The diversity of personal projects also points to a proactive and self-driven individual. However, the lack of explicit team collaboration details in job descriptions makes it difficult to fully assess cultural fit beyond technical contributions.
Soft Skills & Operational Fit
The candidate's career progression from ML Engineer to Lead ML Engineer, Technical Lead, and Co-Founder/CTO roles suggests strong leadership, problem-solving, and strategic thinking abilities. The descriptions of responsibilities like 'Architecture planning' and 'Team leading' indicate operational fit for senior roles. However, without specific psychometric test results or interview data, a detailed assessment of stress handling or team collaboration is not possible.