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• Developed AI/ML solutions to help businesses optimize processes and improve efficiency.
• Implemented fraud detection systems to predict anomalies in transactions.
• Developed demand forecasting models to optimize inventory and supply chains.
• Created customer churn prediction models to analyze data and retain users.
• Built recommendation systems to personalize content and products.
• Conducted sentiment analysis using NLP to detect sentiments.

• Developed and optimized backend functionality using PHP and MySQL.
• Enhanced frontend interface design and user experience with HTML, CSS, and JavaScript.
• Improved page rankings in search engines through SEO optimization.
• Analyzed user behavior to boost conversion rates.
• Automated processes by integrating dealer APIs and data parsing.

• Managed SEO and SEM for website promotion in search engines like Google and Bing.
• Developed content marketing strategies and optimized content for different markets.
• Set up and optimized PPC advertising campaigns on Google Ads and Facebook Ads.
• Analyzed traffic and user behavior using Google Analytics and Yandex Metrica.
• Conducted A/B testing to improve conversion rates through experiments.

• Engineered a SOTA multi-document summarization model for news aggregation, achieving an 87% human acceptance rate with less than 1% critical errors.
• Designed automated news timelines for evolving events, resulting in a 2.8% increase in content depth and a 1.4% boost in user time spent.
• Optimized ranking algorithms with a CTR prediction model, increasing daily active users by 4.3% and user engagement by 2.1%.
• Created a novel similarity scoring formula, improving F1-score from 0.91 to 0.95 for news clustering.

• Developed and deployed text corpus deduplication using a suffix array algorithm on MapReduce, boosting assessor F1-score from 0.77 to 0.82.
• Trained a classifier to improve benchmark coverage, enhancing dataset relevance for pretraining tasks.
• Created a dataset augmentation pipeline with Back Translation, increasing pretraining robustness and generalization.
• Enhanced document parsing quality, resulting in 3% faster model convergence and improved resource efficiency.

• Developed a search robot for products, increasing cold client conversions by 4%.
• Created a report monitoring system for item positions for clients.
• Developed an advanced route-planning algorithm for courier logistics, increasing daily pickup points by 13%.
• Added generation of invoices for product stock, improving product acceptance process speed and accuracy by 15%.

• Implemented processing of all basic data types from Clang AST to equivalent constructions in Eolang.
• Developed a mechanism for translating multidimensional arrays to Eolang.
• Developed a mechanism for translating Enum types to Eolang.

• Built an LLM lead generation assistant for marketing professionals.
• Performed workflow audits and optimized costs by designing a more efficient architecture.
• Automated end-to-end AI pipelines.
• Adapted and prompted LLMs for efficient data processing and content generation.
• Researched methodologies for optimizing AI infrastructure.
• Collaborated closely with Business Development professionals to achieve team goals.

• Developed a system for real-time sentiment analysis automating news data processing.
• Integrated the system with Google Gemini API achieving 100% of project milestones.
• Created an AWS cloud pipeline to predict energy consumption from historical data.
• Delivered fully automated AI pipelines managing to stay within a budget of $500/month.
• Optimized resource allocation to enhance cost-effectiveness.

• Reduced CGI scene creation time by 75% through custom automation add-ons.
• Built reusable procedural geometry and computer vision tools.
• Completed projects an average of 20% ahead of schedule.
• Demonstrated strong collaboration skills with a cross-functional team.
• Worked effectively with up to 5 professionals.

• Automated 90% of Audio/Video system operations, reducing need for on-site support.
• Set up low-latency networks and developed control systems.
• Ensured 100% uptime for media art installations.
• Worked independently and closely with a remote team.
• Fostered a friendly and inclusive environment.

• Replaced legacy VM infrastructure with Kubernetes clusters, reducing infra costs by 30% and improving uptime.
• Designed and rolled out a standardised IAM system using self-hosted Keycloak to decouple from third-party providers.
• Managed distributed bare-metal NoSQL databases for fast-changing data, cutting storage costs by 50%.
• Supported a rapidly growing codebase with 30+ sub-projects through modular cloud-native architecture.

• Implemented a new analytics pipeline using GTM, Meta, and PowerBI — increasing sales by 20%.
• Set up robust CI/CD pipelines for 30+ sub-projects using CircleCI and integrated Jira workflows.
• Helped the team reduce release errors and speed up delivery cycles through process automation.

• Built a functional MVP in 2 months using React, NestJS, and PostgreSQL.
• Defined and deployed system architecture on AWS, including full CI/CD setup.
• Wrote deployment documentation to support handover and onboarding.
• Streamlined development, improving team productivity by 15%.

• Improved UX and performance of an industrial PLM system using Next.js and NiFi.
• Refactored legacy Vue.js project to enhance business process security.
• Built a custom SQL database to support logistics for industrial materials.

I used webscrapped data to create similarity search model

I used vision transformers, data augmention,face detector and deployed the model on AWS SagaMaker

• Collected and preprocessed data to build a time prediction model that improved the accuracy of rendering job estimates.

• Designed and implemented a visual predictive model using synthetic data for internal research.

• Built a sentiment analysis tool to assess user feedback and created a recommendation system based on user behaviour patterns.

• Trained a computer vision model to detect vehicle scratches and damage from images.

• Built a containerised service using Docker for model deployment.

• Enhanced image preprocessing pipeline to boost model accuracy and generalisation.

• Built and maintained backend modules for a rendering SaaS using Python.

• Developed a chatbot to automate communication between technical support and clients.

• Managed and optimised MariaDB and PostgreSQL databases for internal tools.

• Trained and deployed face detection and feature extraction models to production.

• Created APIs and inference pipelines using Triton Inference Server and TensorRT.

• Designed a video stream processing system handling input from multiple cameras.

• Increased vector search performance 20x by optimising FAISS-based similarity search.

• Built dockerised infrastructure for scalable deployment.

• Led development of face and license plate analytics across 4 engineering teams.

• Built ML models for driver identification using sensor data (RF, MLP, DT, KNN).

• Researched video-based action recognition (publication under review).

• Created a facial recognition API using FastAPI and OpenVINO Model Server.

• Supported academic research with practical deployments and experiments

• Led more than 5 research and development projects focused on building human-machine interfaces to control robotic systems via Android apps, WinForms applications, and console tools.

• Conducted research in robotic control and trajectory planning, contributing to academic advancements and real-world implementations.

• Worked on sensor fusion tasks involving PIR, sonar, camera, touch, and gyroscope inputs — integrating and processing data from multiple sources.

• Completed two projects using microcontrollers and single-board computers such as Arduino, PIC32, Raspberry Pi, and Jetson TK1.

• Delivered two working computer vision applications involving object recognition, emotion detection, and a “leader-following” system (robot tracking a moving subject).

• Built a cross-platform mobile app that offers smart outfit recommendations and wardrobe management features.

• Implemented outfit creation tools with a clean, mobile-first UX using React Native and Expo.

• Connected frontend to backend using Supabase and Prisma for rapid, scalable development.

• Designed intuitive logic to support user preferences and seasonality in outfit suggestions.

• Developed and maintained a web application used by over 80 service centres worldwide.

• Contributed to both frontend and backend using React, Next.js, Nest.js, and PostgreSQL.

• Ensured cross-device compatibility and high responsiveness across all major browsers.

• Integrated scalable API services with authentication and database layers.

• Scaled the product from concept to 1M+ registrations, 60K DAU, and 20K MAU in 12 months.

• Managed a cross-functional team of 30+ (Dev, DevOps, GameDesign), introduced Agile workflows and CI/CD improvements.

• Increased average session time by 500% (10 mins → 1 hour) through game balance redesign and reward system revamp (ABC tests).

• Reduced churn rate by 15% using CJM-based onboarding, tracked with Hotjar and Amplitude.

• Localised the product into 8 languages, forming partnerships with local KOLs based on GEO analytics.

• Increased TVL from $5M to $28M (+460%) in 9 months by launching auto-compounding tools and APY incentives.

• Established partnerships with 5 major DeFi protocols to drive liquidity inflow.

• Boosted staking conversion by 45% by simplifying UX (7 steps → 3) and integrating 1-click staking.

• Used Dune Analytics and on-chain user behaviour data to inform roadmap decisions.

• Designed and developed a cross-chain bridge with support for 5 networks, optimising gas usage and reducing transaction costs by 30%.

• Integrated Aave and Uniswap V3, which resulted in 12,000 new users in one quarter.

• Reduced transaction processing time by 40% (12s → 7s) through smart contract refactoring and admin panel cache optimisation.

• Tracked results via Snowtrace and internal block metadata.

• Led the architecture and development of a Data Lakehouse platform for enterprise-scale data storage and analysis.
• Designed and launched a secure component analysis (SCA) system to scan, validate, and deliver safe software artifacts.
• Developed a custom ETL pipeline integrated with Greenplum and Airflow, enabling flexible, reliable data processing.
• Mentored three intern cohorts (Python + Go, DevOps, React) and initiated an internal R&D direction for the company.
• Participated in pre-sales and architectural evaluation of new projects, aligning tech decisions with business needs.

• Built a new development department from scratch, defined internal standards, and established the tech strategy.
• Oversaw in-house development that replaced vendor software with no loss of service quality.
• Successfully migrated two mission-critical systems from Oracle to PostgreSQL, significantly reducing licensing costs.
• Re-architected the company’s DWH, moving 70% of reporting to the new platform for improved flexibility and speed.

• Led architecture and development of several new products: payment aggregator, ticketing platform, parking system, and education accounting tools.
• Developed PL/SQL-based databases and documentation to support operations and compliance.
• Delivered two platforms reaching over 1M MAU.
• Boosted EBIT of the payment platform by 70% after implementing new services.

• Developed UI for a CRM system with integrated Stripe-based payment modules.
• Built a responsive, cross-platform interface.
• Integrated ContentStack CMS and ApolloGraphQL APIs for dynamic content and data fetching.
• Contributed to user account functionality and payment cabinet development in a 21-person team.

• Developed a thematic social platform with game-like functionality.
• Migrated codebase from Angular 8 to Angular 9.
• Integrated calendar API, improved performance (Lighthouse), and implemented SEO meta tags.
• Built responsive templates, multilingual support, and login via Google/Facebook.
• Deployed via Firebase Functions and structured local/session storage.

• Led architectural evolution of a large-scale product using microservices, aligning with business growth and scalability needs.
• Integrated and optimised component testing processes, enabling stable CI/CD and automated release cycles.
• Reduced infrastructure and development costs through architectural review and system optimisation.
• Introduced development and service metrics across the product to improve observability and accountability.
• Actively planned and scoped technical initiatives in collaboration with product owners and multiple teams, ensuring delivery of long-term goals.

• Designed and implemented payment processing flows, including custom gift card authorisation and capture logic.
• Developed auto-reversal services to handle payment anomalies.
• Contributed to admin-facing tools for managing refunds, returns, and layout improvements.
• Integrated Visa Checkout and Amazon Payment, expanding available payment methods.
• Enhanced system maintainability by contributing to REST APIs and backend infrastructure for advertising features.

• Developed detailed customer personas segmented by traffic channel to inform campaign strategy.
• Analysed user behaviour by building funnels and identifying anomalies across website events.
• Created monthly reports evaluating the performance of marketing campaigns, influencing strategic decisions.
• Built data marts in Google BigQuery and Greenplum to support reporting and ad-hoc requests.
• Designed reports from scratch in Looker Studio and Visiology, including migrating dashboards between BI platforms.
• Implemented a Telegram bot with Airflow scheduling and error logging to notify analysts about issues in delayed queries.

• Designed 5+ comprehensive Power BI dashboards for operational performance across departments, with 30+ daily users.
• Built core data marts in PostgreSQL focused on the "order" entity, forming the foundation for company-wide reporting.
• Automated daily, weekly, and monthly data exports for the operations team using Python scripts.
• Conducted regular ad-hoc analysis to support ongoing business needs and decision-making.

As an iOS developer in FG BCS, a leading investment company in the Russian market, I contributed to their app for private investors. We wanted to enable our users to top up the card balance with Apple Pay. There was no direct way to implement this flow, so we had to leverage a third-party service that created an order for the refill amount and transferred the payment to the client’s card using our API. The transaction processing and balance renewal on the screen were imitated.

As an iOS developer in FG BCS, a leading investment company in the Russian market, I contributed to their app for private investors. User was able to enter parameters of an account or a card they wanted to create (currency, type, name, etc) and after confirmation refill it from another card, account or with Apple Pay

Created and developed the application logic for bank product calculators (credits, savings, etc.) from data layer to presentation layer.

Our users received profit for selling their goods and services via our payment gateway in crypto. Many of them wanted to convert this profit into fiat and withdraw it to their bank account. Previously we used a 3rd party service that had a $30.000 threshold for crypto-to-fiat transactions, which prevented our new clients from giving us a try since they couldn’t trust us enough with the amount this high, and SMBs couldn’t afford keeping this amount frozen for so long. I researched and led the integration of alternative service with their API and our UI, that allowed us to lower this threshold to as little as $20 and onboard large clients that previously used our competitor.

The admin side of our service was outdated, lacked cohesiveness due to the initial desire to accelerate time to market, and there were constant complaints about things being hard to find there and simple tasks taking hours. Our business development managers also noticed that users often required personal help with onboarding during calls and wrote mailed similar questions to our support, which meant spending extra time and money. I led the redesign of 14 sections of the personal account, including the payment history, invoices/donations pages, mass payouts, balance top-up/withdrawal, wallets management, and various integrations.

Leveraged best practices to ensure seamless and quick sign-up and onboarding for new users.

Leveraged and combined several payment management systems in the mobile app to receive the desired payment flows: user-platform-user, user-platform-merchant, merchant-platform-user. Optimised the usage of 3rd party APIs and their sequence to receive the lowest possible fee.

Led the creation of an admin panel for a new social media startup from scratch. Took part in creating the project documentation, design, backend and frontend services with a product team. We created the means to manage content and its categories (with a 3rd party tool that helps moderation + the work environment for human moderators), users, payments (payment history, integrations dashboard), notifications, and editorial pages.

◦ Led a portfolio of more than 8 consulting projects and M&A transactions with a combined value of over $120 million ◦ Facilitated a strategic partnership between a Fortune 100 FMCG company and an Eastern European coffee producer, resulting in a doubling of the distribution chain ◦ Prepared exit strategy from a FinTech portfolio business into a leading financial ecosystem with a 3x value growth ◦ Directed a cross-functional team of 6 to develop and implement a 5-year fashion category strategy for a leading Eastern European marketplace to reach top positions in fashion e-commerce ◦ Established a new partnership pipeline with 5 non-competitors, resulting in 8 prospective leads over a 3-month period ◦ Provided ongoing support to the leadership team, including shareholders and the CEO, through comprehensive research and ad-hoc strategy development

◦ Developed and implemented a B2C service for high net worth individuals in the asset management sector from scratch by using product approach and successfully acquired 3 clients ◦ Developed the Russian market expansion strategy for a Swiss technology company and achieved 7% quarterly growth ◦ Created a digital product strategy that increased customer portfolio by 25% for Eastern European investment company

With extensive team discussions I employed three distinct methodologies, namely the Vader sentiment analysis, Bag of Words, and a Hugging Face BERT language model, for the purpose of tweet classification into two categories: "Disaster Tweets" and "Non-Disaster Tweets.". Using BERT-based language models, natural language processing (NLP), data analysis, TensorFlow, and Python programming, i made an in-depth evaluation to determine the optimal approach for the given task.

In collaboration with a fellow Data Scientist, we developed a powerful machine learning model. This model proved to be highly effective in analyzing medical data and accurately predicting whether a patient had a medical condition, achieving a remarkable accuracy rate of over 90%. Using Machine Learning and TensorFlow we facilitated the model's development. Data Analysis and Data Visualization techniques enabled us to gain valuable insights from the medical data, while Python played a pivotal role in implementing and fine-tuning the model, resulting in its impressive predictive accuracy.

Achieved an 80% accuracy rate in classifying celestial objects as Stars, Galaxies, or Quasi-Stellar Objects using a machine learning model that analyzes solar data. It was done through Data Collection, Data Preprocessing, Model Optimization, Iterative Improvement and Documentation.I Gathered a comprehensive dataset of solar data, including various features and attributes. I then Cleaned the dataset by handling missing values and outliers. Further Chosing appropriate machine learning algorithms for classification tasks and then Fine-tune hyperparameters of the model using techniques like grid search or random search to improve its performance. Lastly, Documented the entire process, including data sources, preprocessing steps, model architecture, and results, to facilitate reproducibility and collaboration.

Led the shift of analytical infrastructure, enhancing data resources and decreasing update errors by 90%. Increased identifiable traffic sources from 60% to 95%. Played a crucial role in reducing fraudulent responses from 28% to 1-4% by strengthening moderation and creating a fraud analytics direction. Contributed to a project reducing the cost of applications from groups by 70% and reducing vacancies in central Moscow from 20% to 6%.

Developed an integrated automated online and offline sales analytics system, utilizing various tools like GA, ExpertSender, Dynamic Call Tracking, Naumen, and 1C. Reduced BigQuery costs by over three times and improved the effectiveness of advertising campaigns by 8-10%.