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Valentin

Tech Lead / Architec...
System Architecture
Data Engineering
Mentorship
Migration
Scalability

Tech Lead and System Architect with over 12 years of experience in software development and team leadership. Throughout my career, I’ve built development departments from scratch, led cross-functional teams of up to 60 people, and overseen projects involving complex architecture and high-load systems.

I’ve designed and implemented data platforms exceeding 300 TB in scale, and developed payment systems with over 2 million daily active users and more than 5,000 transactions per second. My focus areas include backend development, data engineering, and system architecture.

I work confidently with Python, Django, PostgreSQL, Greenplum, Kafka, Airflow, Docker, and RabbitMQ. I’m deeply involved in pre-sales, architecture planning, mentoring junior specialists, and aligning tech solutions with business strategy. I thrive in environments where I can combine technical depth with long-term thinking and team growth.

System Architecture
Fintech
Building a Data Lakehouse and Secure Delivery System for Software Artifacts
  • 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.
Migration
Banking
Rebuilding Tech Strategy and Migrating Mission-Critical Systems
  • 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.
High-Load
Transportation
Launching Payment and Ticketing Platforms with High User Load
  • 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.
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Emma

Lead AI & Robotics E... at CleverBotics
Computer Vision
IoT
Robotics
AI
The EU

An AI engineer and robotics enthusiast passionate about bringing technology to life—literally. I specialize in integrating machine learning with robotics, always striving to build devices that feel less mechanical and more human. My projects, like the cheerful Roboista barista robot, reflect my belief that the best technology doesn’t just solve problems—it makes you smile along the way.

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Serzh

Senior Angular Devel... at Upwork
Frontend
Payment Integration
Migration
Performance Optimisation
System Architecture

Frontend Architect & Angular Expert with over 10 years of experience delivering responsive, high-performance web applications and mobile solutions. With a foundation in C programming, microchip design, and data transmission, I bring a deep understanding of systems to the frontend world—especially Angular, which I’ve been working with since its early days.

I've led cross-functional teams, driven architectural decisions, and delivered end-to-end projects from concept to production, including app migrations, SEO optimisation, and UI/UX design. My work spans industries from CRM and payments to social platforms and e-commerce.

Known for my eye for detail and performance, I focus on creating seamless, scalable experiences—whether it's boosting Lighthouse scores, integrating Stripe, or mentoring teams on Angular best practices.

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Aliaksandr

Architect at Reline Management Europe LTD
DevOps
CI/CD
System Architecture
API Design
Backend Development

Architect & Principal Software Engineer with 12+ years of experience designing and building scalable systems, primarily within the .NET ecosystem. Proven track record of leading cross-functional teams, evolving system architecture based on microservices, and optimising infrastructure and development processes. Skilled in building high-load systems, integrating service metrics, and automating CI/CD pipelines. Experience spans industries from fintech to enterprise software, with deep hands-on expertise in .NET 6–8, Kafka, Kubernetes, ElasticSearch, RabbitMQ, and both SQL and NoSQL databases. Passionate about solving complex engineering challenges and driving long-term technical strategy.

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Alexey

Data Analyst at Megamarket
Web analytics
Website traffic management
Website marketing automation
Ad-Hoc Analytics
Business Intelligence

Data Analyst with 2.5 years of experience in building reporting and visualisation solutions using Power BI, Looker Studio, and Visiology.

Proficient in writing complex SQL queries across ClickHouse, Greenplum, and Google BigQuery, with hands-on experience developing data marts in GP and GBQ. Skilled in automating data workflows and creating dashboards with Python. Actively studying modern AI methods with a solid foundation in classical machine learning algorithms. Academic background includes designing data models (star/snowflake schemas) and implementing triggers and transactions.

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Alexander

Co-founder at Askapro
Software Engineering
Fintech
Banking
Investment
Design

With my extensive 7-year background as an iOS engineer, I've demonstrated deep expertise in Apple's iOS platform, mastering both SwiftUI and UIKit. My engagement with various architectural patterns, especially my current focus on the Composable architecture, showcases my adaptability and forward-thinking approach in software development.

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Liubov

Co-founder at Askapro
Business Development
Product management
Product analysis
Monetization
Web analytics

Product Manager with 4 years of international experience across the EU, US, and Asia, specialising in fintech and marketplaces. My background spans both B2B and B2C sectors, with a focus on enhancing usability, managing integrations, and driving growth through product-led strategies for web and mobile platforms.

Business Development
Fintech
Led redesign of 14 pages of a user’s profile in the payment gateway

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.

Business Development
Web3
Onboarding optimisation

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

Product management
Social Media
P2P payment system for a mobile app

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.

Product management
Social Media
Admin panel for a social media startup

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.

Product analysis
Education
Edtech startup features

We implemented automatic certificate generation for course participants, a webinar platform, a new access control system for course modules, and enhanced the pricing model. By identifying and fixing an error that was blocking payments for a specific user segment, we increased the conversion rate to paid plans by 20%.

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Nick

Corporate Developmen... at eCompass
Economics
Fundraising
Go-to-market strategy
Product analytics
Market analysis

I am a enthusiastic and results-driven Corporate Development Manager, who is committed to businesses by creating valuable products and services with global impact. With a wealth of experience in M&A and Strategy development, and a diverse background from investment banking, VC, and e-commerce, I bring a unique blend of skills and expertise to every project I handle.

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Dyimah

Machine Learning Eng... at Freelancer
Tech knowledge
Data analysis
Business Analysis
AI
Data

Machine Learning Engineer with a passion for creative problem solving by combining logic and technical skills with unconventional approaches. My most recent projects, reinforced my skills in data analysis, data pre-processing and model selection/creation utilizing technologies such python, tensorflow, pytorch, and scikit-learn.

Tech knowledge
AI
Advanced NLP Techniques for Effective Classification of Disaster Tweets

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.

Tech knowledge
AI
Development of a High-Accuracy Medical Diagnosis Model Using Machine Learning

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.

Tech knowledge
AI
Developing a Machine Learning Model for High-Accuracy Classification of Celestial Objects

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.

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Madina

Head of Strategic An... at Havas Food
Economics
Team management
Strategic analytics
Data science
Business Analysis

Accomplished analytics professional with 28 years of diverse international experience, a track record of successfully transforming business analytics into an efficient end-to-end Big Data process, and a strong desire to make a difference through the discovery of smart analytical solutions.

Economics
FoodTech
Built a Commercial Business Reporting System from Scratch
  • Gathered a team of BI Analysts and Developers from the scratch
  • Created a data warehouse prototype using Qlik Sense and built a full commercial business reporting system from the ground
  • Complete evaluation of the company's business reporting system, including financial reporting. Sources of financial losses and inefficiency have been identified and quantified.
  • Provided recommendations to the operations office on sales enhancement activities and monitored implementation, which resulted in a significant revenue impact.
  • Built demand forecasting model using XGBoost Regression
Machine learning
BeautyTech
Integration of Automated Machine Learning Model in Sales Support
  • Developed an automated Python Machine Learning model that provides post-evaluation for sales support programs and takes mutual cannibalization into account.
  • Organized and led an ETL developers team that built Avon Russia's Cloud Data Warehouse, the only data source with consolidated and verified business data for operational analytics.
  • With a team of ETL Developers Rebuilt Russian data instance of Global DWH in Snowflake with attached data flow interfaces.
  • Initiated, developed, and implemented new Representative discount system and performance tracking dashboard in Tableau to promote productive sales behaviour
  • Initiated and performed audit of existing business planning processes, suggested ways to improve demand forecasting accuracy
  • Initiated and performed series of strategic analysis on pricing, average order, representatives’ costs and benefits to understand causes behind current business performance and highlighted possible business solutions to the top management and enabled more accurate sales predictions.
Economics
Tobacco
Development of Demand Forecasting process across 6 markets
  • Created a team and built a business insights and analytics function from the scratch
  • Successful converted Marketing Research department to big scale Business Insights function, combining under one roof Marketing Research, Demand forecasting, Trade efficiency analysis & modeling, marketing planning and reporting.
  • Successful development and set up of Demand Forecasting process across all 6 markets.
  • Improvement of deployed Primary Research methodologies and internal data sources.
  • Development and launch of new analytical reporting initiatives.
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Shah

CEO at Time research & innovation
Economics
Product strategy
Stakeholder management
Tech knowledge
Team management

I am Dr Shah Siddiqui, the founder and CEO of Time research & innovation (Tri), Neurodivergent Business Consortium CIC, GenZ Marketing, and an academic. I have a long career and has studied information technology, television production, system engineering, software development, and my PhD was in artificial intelligence. I am experienced running SMEs since 2000 and I am an expert in health tech, business intelligence, digital technology, business development and marketing. Due to work and experienced in technology and business development, I can lay out a technology enhanced business growth, which is mostly needed at current time and future. Without understanding the technology and the A-Z know how, it will be very difficult to sustain. By working with me, you will understand each aspect of the business and can take an applicable decision to get results.

Currently I sit on the board of many companies in the UK to help the CEO and board of directors to expand and grow.

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Alin-Gabriel

Machine Learning Eng... at Deutsche Bank
Natural Language Processing
Machine learning
Data analysis
Artificial Intelligence
Deep Learning

Over 6 years’ experience in Machine Learning and A.I., in all three main specializations, general machine learning, natural language processing and computer vision, with a focus on general machine learning and natural language processing. Experience gained in both research and product projects, while working for companies of renown such as Oracle and Deutsche Bank. Responsible for delivering state of the art A.I. solutions across the globe, in Europe, USA and Asia. Master’s degree in Artificial Intelligence.

Natural Language Processing
Banking
Data Flow Enhancement and Efficient Processing through Large Language Models (LLMs)

In the corporate sector, text data flows swiftly, emanating from diverse sources in various formats, destined for multiple endpoints and actions. This continuous stream of data necessitates management through structuring, making it easy to interpret and analyse, and ultimately directing it to the appropriate user or applying the insights obtained. I utilised several large language models (LLMs) streamline and enhance this process:

  • A question-answering LLM, enabling users to inquire about the content of each document within the flow.
  • A summarization LLM, offering a concise overview of each document.
  • An NLP model for sentiment analysis, determining the sentiment of each document.
  • An NLP model that calculates an absolute similarity score among all documents.
  • Clustering, which groups similar documents together and simultaneously identifies outlier documents.
Natural Language Processing
Banking
ML and DL Solutions for Banking Anomaly Detection

In the dynamic realm of banking, ensuring effective anomaly detection is paramount. Utilising my expertise in state-of-the-art ML algorithms and advanced Deep Learning techniques, I tackled this imperative at Deutsche Bank, a globally recognized leader in financial services. The solution involved several critical stages:

  • Identifying relevant data from various sources.
  • Researching and testing optimal Machine Learning algorithms for tabular data analysis.
  • Exploring and validating appropriate Deep Learning models for extracting insights from textual data (Natural Language Processing).
  • Integrating the resulting models into the rigorous banking environment, complete with all necessary software engineering components: Python, Object-Oriented Programming, Algorithm Design and Complexity, Deployment, and more.
Natural Language Processing
Market Research
Machine Learning and Deep Learning Solutions (NLP) for Automating Market Research Processes

Market research is a domain teeming with diverse data types, including tabular, audio, and particularly text. This wealth of data can be utilised not only to enhance internal processes through automation but also to equip the end client with valuable new functionalities and use cases.

  • The objective of this use case was to automate the labelling of open-ended questions from online market research surveys. Open-ended questions, which receive text responses, require further post-processing to extract useful information. I automated this process for one of the world's largest market research firms using a series of interconnected techniques:
  • Utilising various forms of word embeddings, leveraging both Neural Network models and general techniques.
  • Implementing clustering to group similar responses.
  • Applying summarization and content extraction methods to distil and highlight key insights.
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David

AI&ML Data Scientist at Plymouth Marine Laboratory
Tech knowledge
Project management
Data analysis
Research and Discovery
AI

Highly motivated, enthusiastic, and adaptable individual with valuable experience in project management and academic research, specialising in digital audio. Capable and effective in practical technical roles within the entertainment industry, including organisational and interpersonal aspects of high quality theatre production and live events. Skilled in working with clients to produce brief and deliver creative solutions through implementation of technical infrastructure.

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Grigorij

AI Developer at WildFoundry
Tech knowledge
Data analysis
Prompt engineering
LLM Fine-Tuning
Open-Source LLMs

✅ 4 years of being CTO in a few startups, including https://takzyli.pl. ✅ 6 years of programming experience (Python and others) ✅ Over 2 years of cutting-edge experience in the field of AI development ✅ Been at the forefront of Large Language Models since the very beginning of their boom.

Tech knowledge
AI
Developed an AI-integrated solution that mimics human behavior in social media.

Dating apps, while popular, had users spending excessive hours daily, leading to notable frustration. Research from smalltalks.ai indicated that the average daily usage was a substantial 1.5 hours, with a staggering 70% of users experiencing anxiety post-use. To address this, I developed an application powered by the advanced GPT-4 artificial intelligence. This AI not only mimics human interaction but crafts initial messages based on individual profiles, engages in meaningful conversation, and establishes emotional connections using a meticulously curated pick-up database. Once a rapport is established, it proposes a real-life meeting and notifies the human user, thus streamlining the dating process while reducing user stress.

Prompt engineering
E-Commerce
Crafted a Web App for cosmetics recommendations employing ML and AI technologies.

As CTO at PrimerAI, I developed an intelligent platform for personalized cosmetics suggestions using ML and AI, including OpenCV, GPT-4, and K-means clustering for skin tone detection and categorization. I employed a holistic approach in developing and implementing this web app, which analyzed users' skin tones using computer vision and unsupervised ML algorithms. My contributions covered all aspects of the project, including designing and building the frontend and backend of the web app, as well as administering Linux servers. This ensured a seamless, end-to-end product experience that catered to our users' needs.

Tech knowledge
Trade
Created a streamlined framework GregTrader for automated online trading.

GregTraider is a streamlined framework designed for automated online trading and trading strategy backtesting using historical data. It simplifies the process by allowing users to write a single strategy for both backtesting and online trading, eliminating the need to rewrite and adjust strategies for different platforms. The primary benefit of using Gregtraider is that you only need to write and adjust your trading strategy once for backtesting, and it is immediately ready for real trading. This saves you the tedious work of rewriting and testing your strategy multiple times.

Tech knowledge
Education
Generated educational programming content incorporating a custom GPT API-driven approach for data analysis.

At WildFoundry, I held the role of developer advocate, producing educational programming content through articles and YouTube videos while offering client support. A prominent GPT use case from my experience involved analyzing the apps that users ran on their devices. To overcome the challenge of manually examining tens of thousands of users, I developed a script that scraped user pages one by one and analyzed the content via the GPT API before storing the results in a pandas dataframe. This approach enabled an unbiased and comprehensive analysis of user applications, yielding accurate numbers and insights that outperformed traditional survey methods. The ensuing report allowed the identification of target customer groups and guided the company in shaping its customer relation strategy.

LLM Fine-Tuning
Robotics
LLM-Powered Robot

In this project, I focused on implementing small open-source models, such as Zephir-7b, on single-board computers like the Raspberry Pi. This setup enabled the creation of a robot controlled by an LLM. Working with such compact models presents numerous challenges; one significant issue is the reduced level of intelligence compared to larger models like GPT-4. To address this, the project required fine-tuning the open-source LLM to achieve satisfactory results.

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Kirill

Senior Data Scientis... at Tinkoff
Tech knowledge
Team management
Data analysis
Research and Discovery
Agile

Motivated data scientist with 4 years of experience with Time Series and NLP models. Highly skilled in machine learning, data visualization, DevOps and creative thinking.