Time Series ML Engineer
2021 - 2021Cogsy Limited- Validated and improved the forecasting methodology that powers Cogsy's app.
- Built an in-house Python package for fast experimentation, leveraging Amazon Forecast AutoML, and custom feature engineering.
- Developed ad-hoc predictive models for several of Cogsy's clients.
Technologies: Amazon Web Services (AWS), Python 3, DeepARData Engineer
2020 - 2021Speakeasy Labs- Increased the robustness of the marketing analytics pipeline.
- Helped to define and implemented an event tracking system adapted to the new iOS 14 tracking restrictions.
- Advised the client on specific low-level details related to Segment.io.
Technologies: REST APIs, SegmentMachine Learning Engineer
2020 - 2020Lola Market - Freelance- Developed, deployed, and maintained a ML model to improve the efficiency of the shoppers' fleet.
- Bootstrapped the first data-warehouse and reporting layer in the company (Amazon Redshift, Amazon DMS, and Tableau).
- Developed several dashboards to help the client improve its fleet management efficiency.
Technologies: Amazon Web Services (AWS), AWS, PythonMachine Learning Engineer | Statistician
2020 - 2020Toptal Client- Analyzed financial market valuations in the Gulf region using explainable Machine Learning.
- Wrote a Python package to ensure the in-house reproducibility of each step of the analysis: data processing, data validation, data visualization, model construction, model validation, and model explanation.
- Benchmarked a range of ML solutions and fine-tunned them to enhance model accuracy and explainability.
Technologies: Shapely, Statistics, Scikit-learn, Machine Learning, PythonExplainable AI Engineer
2020 - 202015kay (via Toptal)- Supported the development of a scientific Python package in the medical field.
- Researched applicability of the package inside the open-source ML and AI ecosystem.
- Created tutorial notebooks to showcase potential uses of the package.
Technologies: Explainable Artificial Intelligence (XAI), TensorFlow, Jupyter, PythonData Scientist | Data Engineer
2019 - 2020Goguru Consulting- Deployed the client's first data warehouse and data reporting system.
- Developed components of the analytics stack from scratch using Python, SQL, AWS Redshift, and Tableau Online.
- Developed a Machine Learning model to increase the operational efficiency of Lola Market, a client of Goguru. Lola Market offers its customers the possibility to buy groceries online and have them delivered to their homes in a matter of hours.
Technologies: Random Forests, Scikit-learn, Amazon Web Services (AWS), Tableau, Python, AWS Database Migration Service, AWS, RedshiftData Visualization | Data Engineer
2019 - 2020Cyngn- Created, updated, and maintained the front-end dashboards of the data analytics stack at Cyngn.
- Developed quick visualization prototypes in Tableau and deployed them into dashboards accessible to the engineering team.
- Developed components of the internal ETL tool in Python and SQL.
- Helped back-end engineers integrate front end and back end of the stack inside Amazon Redshift.
Technologies: Amazon Web Services (AWS), SQL, Tableau, AWS, RedshiftMathematical C++ Developer (Genetics Project)
2019 - 2019Confidential- Reviewed and documented the proprietary algorithm that performs base calling.
Technologies: C++, OpenCVMachine Learning Engineer
2019 - 2019Toptal client- Developed statistical and machine learning models to understand the market valuation of financial institutions.
- Created a reproducible pipeline for data science, from data transformation to hyper-parameter model tuning.
- Placed a special emphasis on model interpretability.
Technologies: Scikit-learn, Jupyter, PythonData Scientist | Machine Learning Engineer
2016 - 2019Nordeus- Created a neural network model to generate football player faces in a scalable way. The outputs from this model are used in one of the company's games.
- Designed matchmaking algorithms in Top11 game (a soccer manager simulation with over 200M users worldwide) using game-theory and Monte Carlo techniques.
- Worked with the internal customer support team to automate the process of tagging player complaints using NLP techniques.
- Developed a predictive model to estimate the ROAS (return on ad spend) of the marketing campaigns.
- Managed two junior data scientists responsible for business intelligence and game system design.
Technologies: Scikit-learn, Tableau, Impala, Hadoop, PythonQuantitative Risk Analyst
2012 - 2016Erste Group Bank- Implemented and validated in Matlab and Python all models used by Erste Group Bank to price and hedge interest rate derivatives.
- Wrote exhaustive documentation for each validated model in order to present it to the European Central Bank.
- Proposed and implemented improvements to the methodology used to estimate the credit market risk of the banking and trading books.
- Backtested the performance of different Value At Risk models in order to propose improvements to the methodology used by the bank.
- Mentored junior quantitative risk analysts.
Technologies: MATLAB, Python