Hi, I'm Syed Shams Elahi Ratul👋

Senior QA Automation Engineer · SQA Lead · Applied Data Scientist

Email • LinkedIn • GitHub • Kaggle • QA Portfolio • Data Science Portfolio

👨‍💼 Snapshot

• 🔭 Senior QA Automation Engineer / SQA Lead with 9+ years of experience across Bangladesh, UAE, Canada, and the US.
• 🧪 Architect of enterprise-grade test automation frameworks that reduced testing time by up to 80% and improved team efficiency by 30%+.
• 📈 Applied Data Scientist with hands-on work in ML, DL, NLP & recommender systems, building models that reach 99% accuracy and boosting engagement by 40%.
• 🤝 Trusted by teams in fintech, e-commerce, healthcare, SaaS to bring structure, quality, and speed to delivery.
• 🧭 Comfortable owning end-to-end quality: test strategy, framework design, CI/CD, performance, observability, and coaching junior engineers.

🚀 What I Do

🧪 QA Automation & Quality Engineering

• Design modular, scalable automation frameworks for web, API, and microservices.
• Lead teams through test strategy, risk-based planning, and regression optimization.
• Embed automation into CI/CD pipelines (GitHub Actions, Jenkins, Docker, cloud).
• Drive performance & load testing for high-traffic applications (JMeter, Locust, Artillery).
• Collaborate closely with dev, product, and DevOps to make quality a shared responsibility.

🤖 Applied Data Science & ML for Real Products

• Build classification, regression, clustering & recommendation models with strong business impact (churn, fraud, medical, customer behavior).
• Use deep learning & NLP (BERT, CNNs, Transformers) for text and image problems.
• Deploy models with MLOps best practices (Docker, APIs, monitoring, experimentation).
• Apply data science thinking to testing, observability, and analytics.

🧱 Tech Stack (What I Actually Use)

💻 Languages

🧪 Test Automation & QA

• Test frameworks: Pytest, TestNG, JUnit, Behave/Cucumber (BDD), Cypress test runner
• Test domains: Web, API, microservices, performance, BDD, contract testing

🤖 Data Science, ML & AI

• Areas: classification, regression, clustering, recommendation, NLP, CNNs, LLMs & RAG
• Tooling: Pandas, NumPy, XGBoost, LightGBM, MLflow, Spark, BigQuery, Power BI, Tableau

☁️ DevOps, CI/CD & Cloud

• CI/CD: GitHub Actions · Jenkins · Bitbucket Pipelines
• Infra: Dockerized test suites · cloud-based cross-browser grids (LambdaTest, BrowserStack)

🏆 Selected Highlights

• 💡 Enterprise QA Automation Frameworks
  Designed and led implementation of modular, CI-ready frameworks that power regression, smoke, integration, and performance tests across multiple products.
• ⚡ Massive Productivity Gains
  Automation initiatives cut manual regression by 80%, improved execution speed, and reduced release risk.
• 📊 High-Accuracy ML Solutions
  Delivered ML models (classification, recommendation, NLP) reaching up to 99% accuracy in healthcare, finance, and e-commerce use cases.
• 🌍 Global, Cross-Functional Experience
  Worked with distributed teams in Bangladesh, UAE, Canada, US, aligning QA, dev, data, and product toward measurable outcomes.
• 🤝 Mentor & Lead
  Lead SQA / SQA Automation Engineer, mentoring engineers, standardizing practices, and introducing modern tooling and frameworks.

🌟 Featured Work

🔧 QA Automation & Testing

• Playwright Web & API Automation
  Enterprise-level POM framework, cross-browser coverage, and hybrid UI + API tests to validate microservices end-to-end.

• Cypress UI & Component Testing
  Front-end automation for modern web apps with network stubbing, component tests, and integration with test management tools.

• Selenium & REST Assured Hybrid Framework
  Data-driven, parallelized test suite covering UI + API flows with detailed HTML reports and CI integration.

• Performance & Load Testing
  JMeter / Locust / Artillery suites simulating thousands of concurrent users, integrated into pipelines as quality gates.

🔗 Check more details in my QA portfolio: https://shorturl.at/LtSgS

📊 Data Science & Machine Learning

A large public portfolio of notebooks and projects covering:

• Medical, financial & customer analytics (churn, fraud, risk, survival analysis)
• Recommender systems (movies, books, products, restaurants, music)
• NLP tasks (sentiment analysis, fake news, topic modeling, text classification)
• Computer vision (brain tumor detection, skin disease, image quality classification)
• LLMs & fine-tuning (LLaMA / HF models, RAG, prompt engineering)

🔗 Data Science portfolio (notebooks):
https://github.com/ScarletMcLearn/DataScience/tree/master/Public

📊 Activity (Last 12 Months)

💼 For Recruiters & Hiring Managers

If you’re looking for someone who can:

• Own QA strategy & automation for complex products
• Build frameworks, not just scripts
• Collaborate with engineering, product, and data teams
• Bring data science, ML, and LLMs into your quality & analytics stack

…then we should talk.

📫 Let’s Connect