About Kamil
I’ve always been drawn to problems that look messy at first: too much data, not enough structure, everyone wondering where to start. That’s where I roll my sleeves up and dive in.
Over the past six years, I’ve worked across the energy and tech industries, moving from petroleum engineering into data science and analytics.
Along the way, I’ve built machine learning classifiers with iterative optimization that boosted accuracy and trust, led Agile data projects, and helped teams turn raw data into stories to make decisions.
Lately, I have pivoted towards AI product architecture, leveraging AI-native IDEs to build automated, human-in-the-loop ETL systems while exploring agentic AI and how it can be implemented to derive insights aligned with Sustainability policies while fulfilling client's demands.
I’m fluent in Python, SQL, MS Suite apps, and Power BI, with hands-on experience in machine learning, data curation & digital transformation, exploratory data analysis, prompt engineering, AI automation, and Agile delivery.
Among peers I'm known as 'The Jack of All Trades'.
English
Native or bilingual
Urdu
Native or bilingual
Pashto
Native or bilingual
Remote only
Primarily works remotely
Experience
- Celeron DigitalAI and Machine LearningDIGITAL AND ITApril 2026 - Today (2 months)• • Engineered a "Human-in-the-Loop" ETL platform with dynamic SQLite/PostgreSQL schema generation, multi-role RBAC, and a centralized QC dashboard; integrated real-time analytics to monitor data lineage and model accuracy across the entire pipeline.• • Architected a modular AI-orchestration engine within the ETL platform using Antigravity and Cursor to toggle between Python, cloud APIs(Claude 3 Opus, Gemini Pro), and fine-tuned local/Hugging Face models; enabled flexible, privacy-focused extraction modes for complex technical datasets.
- Viridien GroupData Scientist (Geoscience & Petroleum SME)August 2022 - September 2025 (3 years and 1 month)United Kingdom• • Led an agile curation project through all phases while executing technical workflows (extraction through validation) and delivered over 1.2M technically labelled documents and 273K+ high-quality data rows for software modelling and dashboards.• • Built and optimised KNN and Random Forest classifiers for document-to-page classification, boosting model accuracy from 76% to 92%through active learning, cross validation, and hyperparameter tuning.• • Developed a QC tool to automate data QA cutting stakeholder validation time by 40%, improving SLA by 2 weeks (presented at EAGE2025).• • Automated exploratory data analysis (EDA) using Python, SQL, and Excel (Power Query) that improved the ETL (extract-transform-load) workflow by reducing data preprocessing time by 27%.• • Delivered projects focusing on enhancing data governance – including taxonomy, lineage, data models, integrity, and use cases - whichimproved reporting accuracy and increased commercial stakeholder trust.• • Contributed to AI research initiatives as part of a cross-functional team, utilizing LLMs to automate metadata extraction.• • Led inhouse training sessions on data labelling, improving machine learning models accuracy and streamlining team knowledge transfer.
- TechPet Global ServicesPetrotechnical AnalystMarch 2021 - August 2022 (1 year and 5 months)• • Applied geostatistical correlations to integrate subsurface datasets, improving interpretability of visuals and enabling stakeholders to draw actionable insights more quickly.• • Generated analytical reports and Power BI dashboards highlighting critical metrics (e.g., oil rate, reserves) on reservoir performance.• • Created dynamic reservoir and predictive production models to accurately forecast reserves and production rates.• • Drove strategic stakeholder alignment on critical milestones (e.g., data validation) and status update on reserve and production estimation.
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Education
- MSc Petroleum EngineeringImperial College London2020
- BSc Petroleum & Gas EngineeringBalochistan University of Information Tech Engineering and Management Sciences - BUITEMS2018