Eliott Kalfon
Verified Expert in Engineering
Data Scientist and Machine Learning Developer
Eliott is a passionate data scientist and machine learning (ML) engineer with three years of experience managing and delivering machine learning projects that drive positive organizational changes. He thrives at handling challenging and ambiguous problems, using all tools at his disposal—ML, optimization, statistics—to make data-driven or automated decisions. Eliott's industry experience spans hospitality, life sciences, and healthcare in sales forecasting, pricing, and patient flow prediction.
Portfolio
Experience
Availability
Preferred Environment
Amazon Web Services (AWS), Azure, Visual Studio, Python, SQL
The most amazing...
...machine learning model I've built into production is an hourly sales forecasting model for more than 180 venues to inform staffing and inventory decisions.
Work Experience
Senior Data Scientist
AUTO1 Group
- Developed and deployed machine learning models used throughout the Auto1 Group platforms.
- Monitored deployed machine learning models in terms of business and statistical metrics.
- Engaged with business stakeholders on problem definition.
Data Science Consultant
TrueCue
- Designed a novel machine learning-assisted pricing method for a UK pharmaceutical company yielding a 15% increase in margins.
- Managed the delivery of advanced analytics projects generating more than £100,000 in revenue.
- Developed a linear programming optimization tool to improve raw material allocation for a large Financial Times Stock Exchange 100 Index consumer goods company driving higher product quality and a 12% reduction in monthly waste.
- Contributed as a mentor and organizer to recruitment hackathons, including the TrueCue Women In Data Hackathon (2020 and 2021) and the London School of Economics 2022 Data Science Datathon, aiming to open data science roles to a wider audience.
- Developed dashboards for NHS North West London to monitor hospital bed utilization and COVID-19 patient outcomes in April 2020, used by the hospital administration board throughout the pandemic.
- Built an ML-based auto-dimensional modeling feature for an in-house product using Databricks Notebooks and PySpark.
Experience
Hourly Sales Forecasting for Parkdean Resorts
SQL Server and Python powered the solution. The model was XGBoost, periodically retrained, and re-optimized with a genetic algorithm.
Pricing Opportunity Detection for a Global Pharmaceutical Company
The model leveraged time-series market signal features to detect unusual market conditions and volatility. It then flagged products or SKUs and brought them to the attention of the pricing team.
The model was built and deployed with Python and SQL on a Microsoft tech stack.
Skills
Languages
Python, SQL, R, Java, Python 3
Other
Machine Learning, Mathematics, Optimization, Economics, Game Theory, Statistics, Data Inference, Econometrics, Deep Learning, Natural Language Processing (NLP), Cluster Computing, Distributed Systems, Networks, Data Wrangling, GPT, Generative Pre-trained Transformers (GPT)
Libraries/APIs
TensorFlow, Scikit-learn, Azure Cognitive Services, XGBoost
Tools
Visual Studio, Tableau, Microsoft Power BI, Azure ML Studio
Platforms
Amazon Web Services (AWS), Azure, Jupyter Notebook
Storage
Databases, SQL Server 2017, Redshift, Data Lakes, Azure Blobs, Azure SQL
Education
Master's Degree in Computer Science
University of York - York, United Kingdom
Master's Degree in Management and Strategy
London School of Economics and Political Science - London, United Kingdom
Bachelor's Degree in Economics
Sciences Po - Reims, France
Certifications
Microsoft Certified: Azure Data Engineer Associate
Microsoft
Microsoft Certified: Azure AI Engineer Associate
Microsoft
Tableau Desktop Certified Associate
Tableau
Microsoft Certified: Azure Data Scientist Associate
Microsoft
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