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<!DOCTYPE html>
<html>
<head>
<title>Rohail Taimour</title>
<!-- Open Graph tags -->
<meta property="og:title" content="Rohail Taimour" />
<meta property="og:type" content="website" />
<meta property="og:url" content="https://www.rohailtaimour.com/markdown-cv/" />
<meta property="og:image" content="https://www.gravatar.com/avatar/d199fd8697b01a299af0474947354b8f?s=300" />
<meta property="og:description" content="This is Rohail Taimour's professional CV. Find details about my work, skills, and projects." />
<meta property="og:site_name" content="Rohail Taimour" />
<style type="text/css">
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body,td,tr {
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text-align: left;
font-size: 3em;
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color: inherit;
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.table-cell:last-child {
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/*Entries for CV title and bullets*/
.cv-entry {
margin-bottom: 5px;
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.cv-entry h3,
.cv-entry h4 {
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.cv-entry ul {
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.cv-container {
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width: 100%;
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.sidebar, .main-content {
display: table-cell;
}
.sidebar {
width: 25%; /* This means that this item will take up 25% of the parent container */
background-color: #f4f4f4;
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.competency-value {
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/* Usage: <div class="page-break"></div> */
.page-break {
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</style>
</head>
<body>
<div class="sidebar">
<p style="margin: 0; font-weight: bold; font-size: 18px; color: #bc412b;">
Python Software Engineer | Statistician | AI/Machine Learning Specialist
</p>
<p style="margin: 0;">1040, Brussels, Belgium</p>
<p style="margin: 0;">
rohail.taimour@gmail.com | +32 489 83 64 76 |
<a href="https://www.rohailtaimour.com">Personal website</a> |
<a href="https://www.linkedin.com/in/rohailtaimour/">Linkedin</a> |
<a href="https://github.com/roumail">Github</a>
</p>
<h2>Education</h2>
<div class="sidebar-edu-entry">
<strong>MSc in Statistics</strong> - <span>KU Leuven, Leuven, Belgium</span> - <span>2014-2016</span>
<ul class="sidebar-edu-comments">
<li>Graduated Cum Laude, Master’s thesis on continuous optimization of production processes in MATLAB</li>
</ul>
</div>
<div class="sidebar-edu-entry">
<strong>BSc (Hons.) in Accounting and Finance</strong> - <span>Lahore University of Management Sciences (LUMS), Lahore, Pakistan</span> - <span>2010-2014</span>
<ul class="sidebar-edu-comments">
<li>Graduated with Distinction (3.6/4.0)</li>
<li>Courses: Operations Research, Supply Chain, Decision analysis, Applied Probability</li>
<li>Treasurer for University Adventure Society organizing hiking trips for groups of upto 300 people in North of Pakistan</li>
</ul>
</div>
<h2>Technical competencies</h2>
<table class="competency-list">
<tr class="competency-item">
<td class="competency-key">Programming Languages:</td>
<td class="competency-value">
Python and R with 7+ years of experience
</td>
</tr>
<tr class="competency-item">
<td class="competency-key">Cloud Services:</td>
<td class="competency-value">
AWS (S3, EC2, ECS, Cloudwatch, SageMaker Studio), Azure (Blob, Databricks, Pipelines)
</td>
</tr>
<tr class="competency-item">
<td class="competency-key">CI/CD:</td>
<td class="competency-value">
Git, GitHub Actions, Azure Pipelines, GitHub CLI, Docker, Docker compose
</td>
</tr>
<tr class="competency-item">
<td class="competency-key">Databases:</td>
<td class="competency-value">
PostgreSQL, Redis, SQLite3, Neo4j, SQLAlchemy, Alembic
</td>
</tr>
<tr class="competency-item">
<td class="competency-key">Monitoring:</td>
<td class="competency-value">
Grafana, Sentry, Kibana
</td>
</tr>
<tr class="competency-item">
<td class="competency-key">Code quality tools:</td>
<td class="competency-value">
pytest, coverage, responses, factoryboy, faker, pre-commit, ruff
</td>
</tr>
</table>
<h2>Personal details</h2>
<ul>
<li>Nationality: Belgian, Pakistani</li>
<li>Languages: English (fluent/bilingual), Urdu (Native), French (B1)</li>
<li>Mobility: Driving License available, flexible for hybrid setup in Belgium</li>
<li>Availability: TBD</li>
<li>Hobbies: Drumming and percussion instruments, Bouldering/Climbing, productivity, Squash, reading</li>
</ul>
</div>
<div class="main-content">
<h1>Rohail Taimour</h1>
<h2>Summary</h2>
<p>Seasoned Python Software Engineer with a Master's degree in Statistics. I am proficient in building applications following best software practices such as CI/CD, containerization and operating in an AWS or Azure cloud environment.</p>
<h2>Job History</h2>
<ul>
<li>
<strong>Python Backend Engineer</strong> at Engie GEMS, Brussels, Belgium | <em>Jan 2024 - Present</em>
</li>
<li>
<strong>Python Software Engineer</strong> at Illumina, Mechelen, Belgium | <em>April 2023 - October 2023</em>
</li>
<li>
<strong>Machine Learning Engineer</strong> at GSK Vaccines, Brussels, Belgium | <em>October 2022 - Feb 2023</em>
</li>
<li>
<strong>Lead Data Scientist, AI Developer</strong> at UCB BioPharma, Brussels, Belgium | <em>August 2016 - October 2022</em>
</li>
</ul>
<h2>Relevant Experience</h2>
<div class="cv-entry">
<h3 class="project-title">
Backend Engineering for Green Energy Trading Platform using Flask and Python Ecosystem
</h3>
<div class="table-without-border">
<div class="table-row">
<div class="table-cell">
<p>Python Backend Engineer, Engie Green energy Management solutions (GEMS), Brussels, Belgium</p>
</div>
<div class="table-cell">
<p>Jan 2024 - present</p>
</div>
</div>
</div>
<ul class="project-details">
<li>Support processes for trading wind and solar assets on the European electricity market, as well as manage contract lifecycle as a first line support for incidents and feature requests in a team of developers.</li>
<li>Diagnose incidents using a combination of <strong>Kibana</strong>, <strong>Sentry</strong>, and full coverage of features by testing client workflows instead of unit testing and mocking objects.</li>
<li>Implement endpoints to integrate different services, modularizing legacy code to improve maintainability and reliability.</li>
<li>Enhanced resilience of a scheduled <strong>celery</strong> task making an API call by incorporating retry mechanism. Extended our internal mock for testing celery task execution to support testing that tasks are appropriately retried by monkeypatching celery internals.</li>
<li>Led the migration of two codebases from <strong>SQLAlchemy</strong> v1 to v2. Updated the contributing guidelines to include preferred querying syntax by conferring with the development team.</li>
<li>Setup a scheduled github actions based workflow for integration testing between two services, a database and message queue dependency.</li>
<li>Increased reliability and modularity of CI/CD pipeline in github actions to prevent pull requests being merged into the main branch if they failed certain steps.</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
Python solution enabling launching, pipeline management and automated report downloads for Customer-Uploaded Data
</h3>
<div class="table-without-border">
<div class="table-row">
<div class="table-cell">
<p>Python Software Engineer and Data Pipeline Architect, Illumina, Mechelen, Belgium</p>
</div>
<div class="table-cell">
<p>April 2023 - October 2023</p>
</div>
</div>
</div>
<ul class="project-details">
<li>Designed a Python service that automates the monitoring and processing of customer-uploaded sequencing data, initiating further analysis or report generation based on predefined criteria.</li>
<li>Implemented a dual-layered approach: the first layer handles the initiation and tracking of analysis pipelines, while the second layer is registered as a <strong>Docker</strong> image in the analytics backend to perform post-processing on the output files and create comprehensive summary reports for the customer.</li>
<li>Scheduled the Python service to operate every 30 minutes for new data and updates, ensuring seamless progression from data upload to final report delivery to customer environment.</li>
<li>Implemented comprehensive systems integration, utilizing a combination of CLI tools and API calls for effective coordination and automation across various software components.</li>
<li>Applied Object-Oriented Programming (OOP) principles to organize API, database interactions and endpoint processing to reduce code duplication and utilize self-documenting object names.</li>
<li>Implemented unit testing using <strong>pytest</strong> and implemented fail-safe mechanisms for robust error handling.</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
Automated SQL Script Generation to facilitate PostgreSQL Data Migration in multiple environments
</h3>
<div class="table-without-border">
<div class="table-row">
<div class="table-cell">
<p>Python Software Engineer, Illumina, Mechelen, Belgium</p>
</div>
<div class="table-cell">
<p>July-Aug 2023</p>
</div>
</div>
</div>
<ul class="project-details">
<li>Designed and implemented a data ingestion framework to parse and validate input files for generating and validating SQL update statements.</li>
<li>Conducted comprehensive testing of generated SQL scripts using a mock of production database tables to test that SQL scripts run as expected.</li>
<li>Utilized SQLAlchemy for database schema management, creating and populating mock tables in a test environment to ensure the integrity and functionality of SQL scripts.</li>
<li>Implemented the solution as a Python package encapsulating the entire data migration logic within a Docker entrypoint for portability and ease of deployment.</li>
<li>Leveraged <strong>Jinja2</strong> templating to generate dynamic, parameterized SQL scripts, enabling the script to adapt seamlessly across different deployment environments, such as Development, Integration, and Production.</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
Design and implement information retrieval methods using Natural language processing (NLP)
</h3>
<div class="table-without-border">
<div class="table-row">
<div class="table-cell">
<p>Machine Learning Engineer, IT Supply Quality, GSK Belgium</p>
</div>
<div class="table-cell">
<p>Oct 2022‑Feb 2023</p>
</div>
</div>
</div>
<ul class="project-details">
<li>Improved performance of information retrieval by 20% on unseen test data using a custom named entity recognition (NER) from <strong>Spacy</strong>.</li>
<li>Performed POC’s on Azure DataBricks environment to improve model performance using rule-based techniques as well as <strong>NER</strong> and annotated data to train custom NER.</li>
<li>Added text preprocessing features to the NLP pipeline such as <strong>Spacy</strong> tokenization, Part of speech (POS) tagging, better handling of non‑english emails, breaking emails into sentences, etc.</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
<a href="https://github.com/roumail/powerplant-coding-challenge" target="_blank">Unit Commitment Solver for Power Grid Optimization via FastAPI</a>
</h3>
<ul class="project-details">
<li>Developed a REST API using <strong>FastAPI</strong> for optimizing energy distribution among powerplants based on load requirements and fuel costs.</li>
<li>Implemented multiple algorithms to solve the <strong>unit-commitment problem</strong>, considering factors like fuel cost, powerplant efficiency, and environmental constraints.</li>
<li>Utilized <strong>Pydantic</strong> for data validation and schema definition, ensuring data integrity and streamlined request handling.</li>
<li>Packaged and containerized the application using <strong>Docker</strong>, with detailed documentation and a Dockerfile for easy deployment and scalability.</li>
<li>Employed <strong>pytest</strong>, along with Python best practices such as typing and linting.</li>
<li>Managed project dependencies using <strong>Poetry</strong>, facilitating efficient workflow and package management.</li>
<li>Deployed the API service using <strong>Uvicorn</strong> and integrated a <strong>Swagger UI</strong> for interactive API documentation and testing</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
Yield optimization for batch and continuous production processes using Machine Learning in Python
</h3>
<div class="table-without-border">
<div class="table-row">
<div class="table-cell">
<p>Lead Data Scientist, Supply and Manufacturing, UCB Switzerland/Belgium</p>
</div>
<div class="table-cell">
<p>Aug 2020‑Oct 2022</p>
</div>
</div>
</div>
<ul class="project-details">
<li>Production setting proposed by model directly led to an increased throughput of 20%, turning in a recurring 1.5 million euro in annual cost savings</li>
<li>Analyze time series data collected from equipment sensors and visually summarize golden batch insights</li>
<li>Created (Bayesian) and tree-based regression models to quantify impact of process changes and predict batch performance</li>
<li>Performed a thorough model validation and hyperparameter tuning exercise before recommending model insights be tested in a live production environment</li>
<li>Supported delivery of workshops demystifying the process of conducting AI projects and machine learning to process experts</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
Marketing Mix Optimization and Customer Segmentation modelling in EU5
</h3>
<div class="table-without-border">
<div class="table-row">
<div class="table-cell">
<p>AI/ML engineer, Lead Data Scientist, Go to Market/Commercial EU5, US and Japan, UCB</p>
</div>
<div class="table-cell">
<p>June 2019‑June 2021</p>
</div>
</div>
</div>
<ul class="project-details">
<li>Developed customer segmentation models, identifying key segments for high-potential growth and revenue by integrating multiple data sources to gain a comprehensive understanding of customer interactions and investigate the relationship between customer segments and marketing channel responsiveness.</li>
<li>Optimized marketing resource allocation based on the model’s insights, tailoring marketing strategies to enhance customer engagement and maximize ROI across diverse channels.</li>
<li>Performed feature engineering using <strong>PySpark</strong> and validated ingested data using data visualization methods and discussions with subject-matter experts.</li>
<li>Adapted data science methodologies to address country and product specificities, delivering tailored solutions for up to ten different use cases across various products and countries.</li>
<li>Developed a Python package with <strong>Cookiecutter</strong> templates that abstract the complexities of the data science workflow, enabling configurable deployments across diverse scenarios such as different countries and disease areas.</li>
<li>Enhanced the package to seamlessly wrap over <strong>scikit-learn</strong>, thereby simplifying key data science tasks from preprocessing to model training and tuning.</li>
<li>Incorporated <strong>MLflow</strong> into the package for robust artifact management, allowing for the tracking of model versions, data inputs, and predictions.</li>
</ul>
</div>
<h2>Personal projects</h2>
<div class="cv-entry">
<h3 class="project-title">
<a href="https://github.com/roumail/immoweb-scraper" target="_blank">Web Scraper to analyse Property Purchase and Rental Trends in Belgium</a>
</h3>
<ul class="project-details">
<li>Developed web scraper using Beautiful Soup to collect information such as apartment data such as price, area, etc.</li>
<li>Implemented SQLite for data storage, using <strong>`Pydantic`</strong> for data validation and <strong>`SQLAlchemy`</strong> for database interactions.</li>
<li>Encapsulated the concerns into a python package with dependency management using Poetry.</li>
<li>Employed <strong>Prefect</strong> for job orchestration, managing the workflow's scheduling and monitoring of scraping tasks.</li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
<a href="https://www.rohailtaimour.com" target="_blank">Personal Portfolio and blogging website built using Hugo and hosted using Github Pages</a>
</h3>
<ul class="project-details">
<li>Created website using <strong>Hugo</strong> and implemented features such as a contact form, and visitor commenting capabilities.</li>
<li>Hosted the static website on GitHub Pages and automated the deployment process using GitHub Actions.</li>
<li>Codebase hosted on <a href='https://github.com/roumail/roumail.github.io' target='_blank'>github</a></li>
</ul>
</div>
<div class="cv-entry">
<h3 class="project-title">
<a href="https://github.com/roumail/resume" target="_blank">Automated Resume Builder and Continuous Deployment System with GitHub Pages Hosting</a>
</h3>
<ul class="project-details">
<li>Engineered an automated system for generating, versioning, and hosting a dynamic CV using Markdown, HTML, Jinja templating and CSS.</li>
<li>Set up a trio of GitHub repositories to separately manage the CV's content, styling, and public hosting on Github Pages.</li>
<li>Developed a Python package for automating the styling and generation of the CV, integrating with Markdown and HTML/CSS.</li>
<li>Implemented version control for CV content using a private GitHub repository, ensuring secure and organized data management.</li>
<li>Leveraged GitHub Actions for automating the CV's generation and deployment process, enabling updates through git pushes.</li>
<li>Hosted the final CV on GitHub Pages, providing a live, online version that can be easily updated</li>
</ul>
</div>
</div>
</body>
</html>