Available to hire
Hi, I’m Saeed Parvar. I’m a data scientist with 10+ years of experience in machine learning, statistical modeling, and big data analysis. I turn complex data into actionable insights and AI solutions using Python, R, SQL, and leading ML frameworks to drive measurable outcomes.
I’ve led cross-functional teams, managed projects, and communicated technical concepts to stakeholders. My work spans academia and industry—from HPC simulations to predictive analytics for customer churn, demand forecasting, and optimization. I thrive on solving tough problems and delivering value through rigorous analytics and responsible AI.
Language
Portuguese
Fluent
English
Fluent
Work Experience
Data Scientist at Faculty AI
January 1, 2025 - PresentUtilized Large Language Models (LLMs) to design and deliver interactive coding lessons, enhancing students’ understanding of programming concepts. Developed an intelligent agent to monitor student progress, analyze performance trends, and generate personalized reports for teachers, improving feedback and learning outcomes.
Data Scientist at Extellio
January 1, 2025 - PresentResearched how UI/UX changes impact website KPIs by analysing user behaviour data and applying machine learning to identify patterns and performance shifts. Designed and evaluated A/B test scenarios to measure the effectiveness of interface updates, providing data-driven recommendations to improve engagement and conversion.
Research Associate (Computational Scientist) at Imperial College London
December 31, 2024 - September 26, 2025Developed a statistical model for a boundary layer flow, reducing simulation time from weeks to a single day.
Algorithmic Trading Developer at Freelancer
January 1, 2024 - PresentDeveloped machine learning models to predict financial market movements; backtested classification- and regression-based strategies to evaluate trading signal performance. Mitigated overfitting via walk-forward analysis and parameter tuning. Built a modular algorithmic trading bot trading across crypto, forex, equities, and commodities on Interactive Brokers and Binance; integrated over 130 strategies; improved decision-making speed by 25%.
Postdoc (Senior Simulation Engineer) at Royal Institute of Technology
December 31, 2023 - September 26, 2025Secured research grants including the Euro High-Performance Computing Regular Access Grant, 20 million core-hours, to support large-scale simulations.
Machine Learning Engineer at Freelancer
December 31, 2023 - September 26, 2025Developed ML models (Random Forest, XGBoost, ANN) to predict horse race winners; achieved R² up to 80% through feature engineering, model ensembling and hyperparameter tuning. Implemented ML for customer churn prediction (RF, XGBoost, ANN) with 15% improvement in retention; used ARIMA for NYC CitiBike demand forecasting (25% cost reduction); built NLP sentiment classifier for restaurant reviews (85% accuracy); applied RL to optimize ad CTR for marketing ROI improvements; built CNNs for image classification achieving state-of-the-art performance.
Research Associate (Computational Scientist) at Imperial College London
January 1, 2023 - December 31, 2024Reduced simulation time for a boundary layer flow model from weeks to a day using dimensionality reduction and regression. Applied machine learning to analyze drag force reduction, contributing to a 10% decrease in flight costs.
Machine Learning Engineer at Freelancer
January 1, 2022 - PresentDeveloped, optimized, and deployed ML models (Random Forest, XGBoost, ANN) for predictive analytics across domains—including horse-race outcome forecasting and customer churn—achieving up to 80% R² accuracy and driving a 15% improvement in retention strategies. Implemented advanced time-series forecasting models (ARIMA, Prophet, Exponential Smoothing, XGBoost, LSTM, Gaussian Processes) to predict CitiBike demand and pricing trends, improving forecasting accuracy by 12% and optimizing fleet distribution for a 25% cost reduction. Developed a GPT-2–based crypto commentary generator with automated scraping (Playwright), memory-efficient preprocessing, and domain-specific fine-tuning.
R&D Engineer at INEGI
December 31, 2021 - September 26, 2025Created detailed data visualizations and analyses for Galp Portugal, showing a potential 80% reduction in drag force and associated oil transportation costs.
Postdoc (Senior Simulation Engineer) at KTH Royal Institute of Technology
January 1, 2021 - December 31, 2023Secured Euro High-Performance Computing (HPC) Regular Access Grant for 20 million core-hours. Led a team to develop fluid simulation algorithms (HPC, Fortran, MPI, OpenMP). Used PCA and Regression to analyze bio-fluid flow in complex systems.
Research Assistant at University of Porto
December 31, 2020 - September 26, 2025Developed a model to simulate jet flow on HPC clusters, resulting in a 20% increase in computational efficiency (utilizing PCA, Regression, and Association Rule Learning).
R&D Engineer at Institute of Science and Innovation in Mechanical and Industrial Engineering
January 1, 2020 - December 31, 2021Developed analytical solutions, reducing computational costs from days to under a minute. Conducted exploratory data analysis to uncover an 80% drag force reduction, cutting oil transport costs (Galp Portugal).
Research Assistant at University of Porto
January 1, 2017 - December 31, 2020Developed models and algorithms for jet flow simulations, boosting HPC efficiency by 20%. Created a post-processing toolbox for heat transfer analysis, improving cooling efficiency of electronic equipment by 8%. Researched renewable energy sources, advancing sustainable energy technologies.
Education
Ph.D. in Mechanical Engineering at University of Porto, Portugal
January 11, 2030 - September 26, 2025Ph.D. in Mechanical Engineering at University of Porto, Portugal
January 11, 2030 - March 9, 2026Qualifications
M.S. in Aerospace Engineering
January 11, 2030 - September 26, 2025Cryptocurrency Algorithmic Trading with Python and Binance
January 1, 2024 - September 26, 2025Algorithmic Trading and Finance Models with Python, R, & Stata Essential Training
January 1, 2024 - September 26, 2025Python for Finance: Investment Fundamentals & Data Analytics
January 1, 2024 - September 26, 2025Machine Learning A -Z: AI, Python & R + ChatGPT
January 1, 2023 - September 26, 2025Algorithmic Trading and Finance Models with Python, R, & Stata Essential Training.
January 1, 2024 - March 9, 2026Python for Finance: Investment Fundamentals & Data Analytics.
January 1, 2024 - March 9, 2026Project Management Foundations.
January 1, 2024 - March 9, 2026Machine Learning A -Z: AI, Python & R + ChatGPT.
January 1, 2023 - March 9, 2026Industry Experience
Financial Services, Software & Internet, Professional Services, Education, Other
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