Machine Learning Engineer2021 - PRESENTEasyHealth
Technologies: Google Cloud Platform (GCP), Python
- Developed ML-based bidding bot to acquire leads more cost-effectively.
- Developed a churn prediction model to anticipate policy churn and increase customer retention.
- Built a simulation engine to optimize key parameters for daily operations.
Time Series ML Engineer2021 - 2021Cogsy Limited
Technologies: Amazon Web Services (AWS), Python 3, DeepAR
- 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.
Data Engineer2020 - 2021Speakeasy Labs
Technologies: REST APIs, Segment
- Increased the robustness of the marketing analytics pipeline.
- Helped define and implement an event tracking system adapted to the new iOS 14 tracking restrictions.
- Advised the client on specific low-level details related to Segment.io.
Machine Learning Engineer2020 - 2020Lola Market - Freelance
Technologies: Amazon Web Services (AWS), AWS, Python, Scikit-learn
- Developed, deployed, and maintained an ML model to improve the efficiency of the shoppers' fleet.
- Bootstrapped the company's first data warehouse and reporting layer, including Amazon Redshift, Amazon Database Migration Service (DMS), and Tableau.
- Developed several dashboards to help the client improve its fleet management efficiency.
Machine Learning Engineer | Statistician2020 - 2020Toptal Client
Technologies: Shapely, Statistics, Scikit-learn, Machine Learning, Python
- 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, including data processing, data validation, data visualization, model construction, model validation, and model explanation.
- Benchmarked a range of ML solutions and fine-tuned them to enhance model accuracy and explainability.
Explainable AI Engineer2020 - 202015kay (via Toptal)
Technologies: Explainable Artificial Intelligence (XAI), TensorFlow, Jupyter, Python
- 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.
Data Scientist | Data Engineer2019 - 2020Goguru Consulting
Technologies: Random Forests, Scikit-learn, Amazon Web Services (AWS), Tableau, Python, AWS Database Migration Service, AWS, Redshift
- 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.
Data Visualization | Data Engineer2019 - 2020Cyngn
Technologies: Amazon Web Services (AWS), SQL, Tableau, AWS, Redshift
- 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.
Mathematical C++ Developer (Genetics Project)2019 - 2019Confidential
Technologies: C++, OpenCV
- Reviewed and documented the proprietary algorithm that performs base calling.
- Advised the client on how to improve the current algorithm.
- Debugged the code and proposed improvements to increase accuracy.
Machine Learning Engineer2019 - 2019Toptal Client
Technologies: Scikit-learn, Jupyter, Python
- 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.
Data Scientist | Machine Learning Engineer2016 - 2019Nordeus
Technologies: Scikit-learn, Tableau, Impala, Hadoop, Python, Data Analyst
- 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 the Top Eleven game, a soccer manager simulation with over 200 million 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 marketing campaigns' ROAS (return on ad spend).
- Managed two junior data scientists responsible for business intelligence and game system design.
Quantitative Risk Analyst2012 - 2016Erste Group Bank
Technologies: MATLAB, Python
- 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 to present 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 to propose improvements to the methodology used by the bank.
- Mentored junior quantitative risk analysts that joined the team.