Hichem Elfertas
Senior Data Scientist
Experience
Senior Data Scientist
Shurgard
- Suggested, designed, and developed end-to-end machine learning and advanced analytics solutions with the Data & AI Team to increase revenue or reduce cost.
- Led migration of all developed ML models and tools to the Databricks platform.
- Ensured smooth production deployment of ML products, optimizing for scalability and performance.
- Successfully migrated and deployed ML products to a robust, scalable platform.
- Improved model performance and reliability in production, enabling more efficient data-driven decisions.
- Developed an AI agent capable of performing text classification and sentiment analysis on customer reviews.
- Created visualizations of sentiment analysis results to provide actionable insights to the business.
- Automated generation of sentiment analysis reports and integrated them into existing systems.
- Eliminated the need for third-party sentiment analysis services, resulting in cost savings.
- Provided direct access to sentiment insights, enhancing decision-making capabilities.
- Designed and developed a predictive model to identify clients likely to end contracts based on visitation patterns, contract features, and customer profiles.
- Integrated the predictive model into operational workflows, enabling store managers to take timely retention actions.
- Collaborated with stakeholders to align the model with business goals and engagement strategies.
- Provided store managers with actionable insights to increase customer retention.
- Enhanced long-term client relationship maintenance, contributing to sustained revenue.
- Supervised a data science intern’s master’s project by guiding coding, machine learning techniques, and providing relevant business insights.
- Supported successful completion of the intern’s project and enhanced practical skills.
- Technologies: Python, PySpark, SQL, Azure Databricks, Azure DevOps, VSCode.
- Methodology: Agile.
Data Scientist
Shurgard
- Worked within the Pricing Team on developing a new revenue management tool.
- Designed the data model to feed machine learning models and pricing workflows for a multi-country pricing model across seven European countries.
- Developed a pricing model based on microeconomic theory, incorporating factors like supply, demand, and customer lifetime value.
- Implemented a comprehensive testing strategy to measure and validate the model’s performance.
- Created monitoring workflows to ensure continuous performance of the pricing model.
- Increased revenue generated by new customers by 6.8% and achieved adoption by 60% of warehouses in targeted countries.
- Designed and developed a rate increase model using survival models and customer lifetime value analysis.
- Established a testing strategy and built workflows to monitor the rate increase model’s effectiveness.
- Increased revenue from existing customers by 5% and applied the model to 80% of the existing customer base.
- Developed ML tools to forecast revenue for new warehouses and acquisitions, supporting investment decisions.
- Created and integrated an optimization tool to enhance warehouse unit mix, improving space utilization.
- Improved investment decisions with accurate revenue predictions and boosted ROI through optimized unit mix.
- Conducted in-depth analyses to uncover trends and provided data-driven recommendations to the Pricing Team and executives.
Data Scientist
Carrefour Finance
- Generated actionable insights using analytics techniques and machine learning within the Marketing Department.
- Developed an RFM segmentation and migration matrix using SAS.
- Performed on-demand customer behavioral analysis using SAS.
- Contributed to product development by deciding messages and offers for each customer.
- Made recommendations to improve customer selections and A/B tests.
- Evaluated marketing campaigns and fidelity programs.
- Developed and automated dashboards.
- Developed a churn model to improve customer retention.
Risk Modeler
Euler Hermes
- Worked on producing internal reporting for group entities’ risk metrics within the Capital and Risk Management Department.
- Created and enhanced tools for risk calculation and monitoring.
- Produced monthly and quarterly risk reporting.
- Documented the risk metrics production process.
- Performed data reconciliation from different sources.
SAS Developer
AXA Belgium
- Contributed to a DataMart shift by updating and developing SAS macro programs to produce performance analysis of investments.
- Produced performance analysis by updating and adapting existing SAS macro programs according to the new DataMart.
- Developed new SAS macro programs to enhance and optimize the performance analysis process.
- Tested performance analysis accuracy in coordination with the middle office team.
Pension Investments Analyst
Sanofi European Treasury Center
- Advised five pension governance bodies in three European countries on investment activities, regulations, and tax optimization.
- Monitored investments of eight pension plans with a €2.5 billion portfolio.
- Provided performance analytics and communicated findings to investment country managers and fund trustees.
- Performed due diligence, quantitative and qualitative analysis for fund and manager selections.
- Provided investment-related studies for management and trustees.
- Benchmarked pension fund performance and allocation.
- Supported reconciliation, verification, and communication of fund performances.
Equity Strategist
Société Générale Private Banking
- Assisted strategists in making investment recommendations, building macroeconomic scenarios, and monitoring equity markets.
- Developed a new tool reflecting real Chinese economic growth.
- Enhanced and developed equity valuation tools (risk premium, Shiller PE ratio).
- Conducted on-demand economic analysis for clients and portfolio managers.
Operational Risk Analyst
Natixis Global Asset Management
- Assisted risk managers in monitoring and quantifying operational risk for over thirty asset management firms.
- Designed and documented a method for quantifying operational risks (Advanced Approach) using R.
- Conducted annual risk measurements and stress tests for regulatory purposes.
- Developed operational risk maps for five new private equity firms.
- Automated risk quantification processes.
Summary
Senior Data Scientist with 10+ years of experience designing and deploying machine learning, advanced analytics, and AI-driven solutions.
Proficient in Python, PySpark, SQL, SAS, and R, with extensive experience in Azure Databricks for large-scale data processing and Azure DevOps for agile project delivery and version control.
Skilled in Deep Learning (TensorFlow) and Generative AI Engineering (Databricks), with hands-on expertise in GPT models, Retrieval-Augmented Generation (RAG), LangChain, Hugging Face ecosystem, and OpenAI APIs.
Passionate about leveraging machine learning and Generative AI to develop scalable, value-driven solutions that enhance business performance and decision-making.
Skills
- Python
- R
- Sas
- Sql
- Pyspark
- Vba
- Databricks
- Azure Devops
- Ensemble Algorithms - Bagging (Random Forest)
- Ensemble Algorithms - Boosting (Adaboost, Gradientboosting, Xgboost)
- Vscode
- Git
- Python (Numpy, Pandas, Scikit-learn, Pytorch, Tensorflow, Nltk)
- Genai
- Rag
- Gpt
- Hugging Face
- Ai Agents
Languages
Education
Paris Dauphine & Pantheon Assas University
Master statistical & financial engineering · Statistical & financial engineering · Paris, France
Law School, Algiers University
Bachelor in law · Law · Algeria
National School of Statistics and Applied Economics
Engineer in applied statistics · Applied statistics · Algeria
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