About Md Alqurayish
Data Scientist and Product Manager helping SaaS companies turn data into business decisions and launch products from idea to live market. Five years of remote experience across the UK, Germany, UAE, and US, shipping work for hospitality, fintech, automotive, and AI clients.
What I do for clients:
Data Analytics & Storytelling, I build the reporting and analytics layer that helps teams make better decisions. Past work includes building 45+ Looker Studio dashboards for a UK workforce platform managing 800+ staff across 81 clients (reducing payroll errors by 25%), and analyzing 1M+ user events at a Bangladesh fintech to identify the highest-LTV acquisition cohort (delivering a 15% retention ROI lift in four weeks).
Product Management & Launches: I take SaaS products from concept to live market. At Plagit (UAE), I led a hospitality SaaS from discovery through GA launch, owning PRDs, sprint planning, AWS infrastructure, UAT, and the GA release with a team of 5+ working remotely across three continents. System uptime improved 25% in the first three months.
AI & LLM Solutions: Through D-SAi (my AI studio), I build production-ready AI agents, RAG pipelines, Business automation, and prompt engineering systems. Most recently, I worked as an LLM Evaluator at Turing, applying SxS evaluation frameworks for foundation model training pipelines.
How I work:
Hands-on, async-first, and used to working across time zones. I write clear documentation, set clear expectations, and ship on the timelines I commit to. I work best with founders and product leaders who need someone who can own outcomes, not just produce deliverables.
Typical engagements:
SaaS product launches (idea-to-market)
Data analytics setup and dashboard development
LLM evaluation pipelines and AI agent builds
Product strategy and PRD writing for AI features
Analytics audits and KPI framework design
Open to short, medium, or long-term projects.
English
Fluent
German
Basic
Arabic
Basic
Bangla
Native or bilingual
Remote only
Primarily works remotely
Experience
- D-SAi - Data Science & Software Development CompanyData Scientist • · Product ManagerJanuary 2025 - Today (1 year and 7 months)on a project software data business end-to-end scoping to deployment.• • Built AI automation pipelines using LLM Agents, RAG architectures, and prompt engineering for client projects, automating complex business workflows and reducing manual process overhead.• • Delivered end-to-end Data Science solutions for clients including predictive modelling, automated data pipelines, and interactive BI dashboards, translating raw data into actionable business intelligence.• • Spearheaded software development project delivery, owning requirements, architecture decisions, sprint planning, and client stakeholder management across the full development lifecycle.
- Analytic Company GmbHData AnalystJuly 2022 - Today (4 years and 1 month)Germany• • Engineered high-accuracy automotive datasets using SQL, Excel, and JavaScript regex constraints, delivering 7+ validated datasets monthly with 100% data integrity across European markets.• • Accelerated data completeness by 100% through systematic gap research and vehicle model validation, filling missing values across US, CA, DE, ES, PT, FR, IT, IR, NL and UK market catalogues.• • Executed quality assurance audits, including data comparisons, consistency checks, and model-level validation, reducing downstream reporting errors and supporting precision pricing decisions.• • Managed end-to-end data pipeline: ingestion, cleaning, transformation, and entry into production systems, maintaining zero defect data integrity standards across all deliverables.
- TuringBusiness Analyst - LLM EvaluatorJanuary 2026 - April 2026 (3 months)United States• • Evaluated 100s of LLM outputs weekly using the SxS/GHD framework, scoring helpfulness, correctness, safety, and instruction-following, directly improving model training data quality.• • Detected hallucinations and factual inconsistencies using structured fact-checking workflows, writing high-quality rationales that reduced label noise and sharpened model behaviour at scale.• • Applied evaluation rubrics consistently across diverse prompt categories, supporting AI training pipeline reliability for large scale commercial LLM development programmes.
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Education
- B.Sc. in Electrical & Electronics Engineering (EEE).Varendra University2018B.Sc. in Electrical & Electronics Engineering (EEE).
Certifications
- Moving: Data Analyst → Data ScientistLinkedIn Learning2026