QA Analysis
Requirements analysis, planning, user stories, defect lifecycle management, and reporting. Analyzing and translating business needs into acceptance criteria.
Quality.✓ Intelligence.✓ Insight.✓ Markets.✓
QA Analyst with a background in tech, financial markets and AI. Proven experience in Business Intelligence, SaaS, HRM and eCommerce projects across international remote teams.
01
Quality Assurance
Testing
Functional, regression, exploratory, usability, acceptance, A/B, smoke, black-box, mockup compatibility including GUI-RDW aspects and AI in the process.
Agile & Collaboration
Sprint cycles and remote work across international teams in the US, EU and Asia. Close collaboration with dev, product and design to prioritize and deliver.
UX / UI
Providing user experience and interface insights with actionable recommendations to product and development teams.
Cross-Platform Testing
Multi-device, browser and OS-level compatibility testing. Ensuring consistent experiences across screen sizes. Web, desktop, apps.
Documentation
Guidelines, documentation, use-test cases coverage, and reports.
02
Artificial Intelligence
AI Usage
Large language models on a daily basis — prompting, research, calculations, context management, business insight extraction and output validation.
AI Oversight & Supervision
Assessing the accuracy, consistency and logic of AI-generated results. Human-in-the-loop review practices to keep AI-assisted processes reliable.
Productivity
Identifying tasks where AI can be useful — creating documentation, reports, summaries, and transforming data into visual formats.
AI-Augmented QA
Using AI to explore websites and check usability, create reproduction steps, detect differences, identify specific content, uncover errors and get guidance on improvements.
Responsible AI Practices
Understanding AI limitations and ethical considerations. A structured approach to validating AI outputs before they reach production or final decisions.
AI Cycle
Using AI to enhance reports and results based on developed guidelines — creating new, updated content and verifying it against multiple sources.
AI / LLMs · usage
Grok+High
Anthropic - ClaudeMid+
Gemini, Flux etc.Mid
03
Financial Markets & Analysis
- Traditional Finance
- Stocks, Equities, ETFs, CFDs, Indices
- Commodities
- Metals, Energy, Agricultural Futures
- Centralized Finance
- Regulated Traded Digital Assets
- Time Zones
- CET–EST · Nasdaq, NYSE, LSE, Xetra, GPW
- Foreign Exchange
- Forex, Currency Pairs
- Platforms
- Brokerage Platforms, TradingView and more
- MetaTrader
- MQL4/5, EA algo strategies, multi-timeframe
- Decentralized Finance
- DeFi, NFT, Web3 Tools and more
- AI
- Research, Data Dashboards, Charts, SWOT
- Education
- Master's Degree in Economics
Technical Analysis
Chart pattern recognition, price action, trend lines, indicator-based analysis, signal evaluation across multiple timeframes.
Fundamental & Macro Research
Earnings reports, economic data releases, geopolitical events, sector rotation and market sentiment.
AI-Assisted Market
Leveraging AI to accelerate market research: news summarisation, sector and earnings-call analysis, screening for opportunities at scale, improving algo strategies.
Human Part
Systematic review of financial instruments, drawing conclusions from observed data, adaptive decision-making and contextual intuition.
Chart-Based Setups
Adaptive rule-based setups with entry levels, stop-loss, resistance, support and take-profit criteria.
Risk & Portfolio Mgmt
Position sizing, diversification, correlation, volatility metrics, and structured approaches to managing downside in uncertain markets. Long-term positioning.
04
Vibe Designing
05
Overall Career Experience - Highlights
- Data aggregation, business specifications, planning, reporting, data visualization, and new feature planning.
- Ensured quality across platforms and modules to validate functionality and cross-platform consistency.
- Managed product backlog, updated guidelines, refined acceptance criteria, prioritized tasks and provided UX/UI suggestions.
- Improved prompts and phrases for AI software and machine learning applications based on data and requirements.
- Data-driven BI reports, dashboards, market trends; AI prompting to enhance research and business insights.
- Online payment processes, newsletters, content editing, mailing and marketing.
- Equities, commodities, Forex, CFDs, ETFs, other digital assets. Fundamental and technical analysis.
- MQL algo strategies based on own parameters, indicators, and AI-assisted EA development.
06
Let’s connect.
Open to new opportunities and projects — Europe and Worldwide.
✉ Contact via details provided in the CV