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Stock trading industry: Trading Strategy Research and Development (portfolio available upon request).• Developed an algorithmic day trading strategy backtester / Risk & PnL engine for stocks to facilitate signal research:o Ingested and processed historical data into the PostgreSQL database, calculating multiple technical indicators using Python.o Designed and fine-tuned a machine learning model, achieving significant improvements in risk and profit metrics compared to a naïve… Show more Stock trading industry: Trading Strategy Research and Development (portfolio available upon request).• Developed an algorithmic day trading strategy backtester / Risk & PnL engine for stocks to facilitate signal research:o Ingested and processed historical data into the PostgreSQL database, calculating multiple technical indicators using Python.o Designed and fine-tuned a machine learning model, achieving significant improvements in risk and profit metrics compared to a naïve benchmark.o Enabled backtesting of various scenarios, including the impact on ROI and Risk based on parameters such as candle frequency, model training window, variables used during machine learning training, slippage value, end-of-day trading session, and mix of short/long positions. Risk metrics: Sharpe, Sterling, Sortino and Max drawdown.• Operationalized the optimal strategy and scenario:o Automated and containerized ETL pipelines for data ingestion and processing using Python, PostgreSQL, Docker, and Airflow, ensuring timely and modular data capture, improving the efficiency of trading decisions. Show less

Hedge Fund Industry: Trading Strategy Research and Development.• Developed a Proof of Concept (POC) leveraging machine learning to enhance decision-making in a trading strategy for the futures market of a Confidential Hedge Fund.

Wealth Management industry (a major Canadian bank): Data flow pipeline automation for KYC regulation.• Migrated a dataflow to AWS for KYC regulations, supporting 850 wealth advisors across Canada:o Mapped and coded transformation rules from on-premise databases to AWS using SQL.o Assessed data quality pre-migration (data profiling), ensuring all scenarios were addressed with business owners, reducing legal penalties by resolving unknown and consolidating investor profiles at the… Show more Wealth Management industry (a major Canadian bank): Data flow pipeline automation for KYC regulation.• Migrated a dataflow to AWS for KYC regulations, supporting 850 wealth advisors across Canada:o Mapped and coded transformation rules from on-premise databases to AWS using SQL.o Assessed data quality pre-migration (data profiling), ensuring all scenarios were addressed with business owners, reducing legal penalties by resolving unknown and consolidating investor profiles at the individual level.o Applied machine learning to reconcile free-form text data, significantly improving data quality.o Contributed to AWS data migration using DMS with load timestamps, enabling auditability and quick reconciliation.o Led knowledge transfer sessions for two data analysts, providing expertise on data domains. Show less

Energy Management industry (a Fortune Global 500 company) : Data flow pipeline automation.• Migrated a dataflow to Google Cloud Platform (GCP), utilized by one of the world’s largest hospitals across multiple sites:o Developed ETL scripts in Python to extract data from sensors in Building Management Systems' on-premise databases into GCP BigQuery (data warehouse), resulting in projected annual energy savings of up to $200K.o Created Python scripts to automate the tracking of… Show more Energy Management industry (a Fortune Global 500 company) : Data flow pipeline automation.• Migrated a dataflow to Google Cloud Platform (GCP), utilized by one of the world’s largest hospitals across multiple sites:o Developed ETL scripts in Python to extract data from sensors in Building Management Systems' on-premise databases into GCP BigQuery (data warehouse), resulting in projected annual energy savings of up to $200K.o Created Python scripts to automate the tracking of data quality issues in sensors, saving the energy team 40 hours per month. Show less

Created tools to develop an Algorithmic Day Trading Strategy for Stocks.• Developed analytical routines leveraging machine learning (time series clustering) to generate and backtest trading signals using Python. These routines would be elementary blocks used later on to manage my own stocks portfolio.

Telecommunications and Media Industry (a major Canadian player): Client Knowledge Project - Understanding customer behavior through the application of clustering algorithms.• Developed a clustering algorithm to analyze client consumption patterns, including YouTube video app usage, leveraging Comcast’s user session-level data feed; adopted enterprise-wide by marketing teams for improved audience targeting:o Processed and aggregated large datasets (100M+ records) using parallelized… Show more Telecommunications and Media Industry (a major Canadian player): Client Knowledge Project - Understanding customer behavior through the application of clustering algorithms.• Developed a clustering algorithm to analyze client consumption patterns, including YouTube video app usage, leveraging Comcast’s user session-level data feed; adopted enterprise-wide by marketing teams for improved audience targeting:o Processed and aggregated large datasets (100M+ records) using parallelized processing Pyspark/Cloudera to feed a clustering algorithm and evaluate model quality, resulting in improved cross-sell and upsell campaigns.• Extracted and analyzed insights from a Next Best Offer Neural Network model:o Developed a Tableau dashboard to monitor campaign performance and operational efficiency.o Built MLOps model drift and data drift dashboards on Cloudera using PySpark to track model and data quality. Show less

Facility and Energy Management Industry - two Canadian sites of a Fortune 500 company including one of the world’s largest hospitals.• Led reporting and data engineering initiatives for internal operations: o Collaborated with various teams to define KPIs and gather requirements for reporting during workshops and business user acceptance testing (UAT).o Created efficient, intuitive and easy-to-maintain dashboards in Tableau / SQL for multiple business lines, leveraging data from… Show more Facility and Energy Management Industry - two Canadian sites of a Fortune 500 company including one of the world’s largest hospitals.• Led reporting and data engineering initiatives for internal operations: o Collaborated with various teams to define KPIs and gather requirements for reporting during workshops and business user acceptance testing (UAT).o Created efficient, intuitive and easy-to-maintain dashboards in Tableau / SQL for multiple business lines, leveraging data from SAP, Maximo resulting in $1.6M annual savings for Purchasing, Finance and Performance Control departments.• Led a self-service BI initiative, providing business lines with Tableau development training and access to automated Tableau Server data sources consolidated through complex SQL queries and stored procedures, resulting in a time savings of 15 hours a month.• Contributed to the integration of the Maximo application into AWS datalake in collaboration with data architects.• Automated critical monthly reports (energy consumption, performance control) using Tableau, saving 20 hours per month and ensuring data persistence of manual entries into databases.• Collaborated in designing data marts in GCP for monthly energy reports.▪ Energy management project: Created Python application connector to ingest energy meter data into an energy management software.▪ Automation projects: Created automated scripts to extract information from unstructured data,reconcile data between different sources using machine learning tools in python. Show less

Automotive industry (US-Canadian network of dealerships): Developed a classification Machine Learning model to predict the likelihood of a sale after a car price drop.▪ Documented, coded a model using Scikit-learn in Python and collaborated with team members on Github.▪ Managed milestones ' project in Agile mode with Asana.▪ Created the pipeline to put the model into production on Google Cloud Platform.▪ Led a data science team of 2 members for data visualization and… Show more Automotive industry (US-Canadian network of dealerships): Developed a classification Machine Learning model to predict the likelihood of a sale after a car price drop.▪ Documented, coded a model using Scikit-learn in Python and collaborated with team members on Github.▪ Managed milestones ' project in Agile mode with Asana.▪ Created the pipeline to put the model into production on Google Cloud Platform.▪ Led a data science team of 2 members for data visualization and delivery.▪ Additional Project: Helped writing AI related business proposals based on Recommender Systems using industry standards. Show less

Tax Advisory Industry: Management and tracking of tax payments for cryptocurrency portfolios.▪ Won a K$ 10 award in a team of 4 people within a Fintech organization.▪ Developed a web application to manage cryptocurrency transactions and calculate tax payments, featuring a fully functional user interface, error handling and database design using Django and Requests to scrap blockchain data.▪ Prepared the pitch and pitched the Value Proposition to the Vice Prime Minister of… Show more Tax Advisory Industry: Management and tracking of tax payments for cryptocurrency portfolios.▪ Won a K$ 10 award in a team of 4 people within a Fintech organization.▪ Developed a web application to manage cryptocurrency transactions and calculate tax payments, featuring a fully functional user interface, error handling and database design using Django and Requests to scrap blockchain data.▪ Prepared the pitch and pitched the Value Proposition to the Vice Prime Minister of Québec and banking professionals. Show less

Telecommunications and Media Industry (a major Canadian player): Developed a classification Machine Learning model to predict subscription likelihood, enhancing marketing effectiveness.▪ Interacted with the Project Manager and the client to develop the data model with relevant data sources, gave feedback about data quality▪ Created the analytical base in an automated fashion and used statistical algorithms in SAS/SQL: feature selection and creation of KPIs, application of a logistic… Show more Telecommunications and Media Industry (a major Canadian player): Developed a classification Machine Learning model to predict subscription likelihood, enhancing marketing effectiveness.▪ Interacted with the Project Manager and the client to develop the data model with relevant data sources, gave feedback about data quality▪ Created the analytical base in an automated fashion and used statistical algorithms in SAS/SQL: feature selection and creation of KPIs, application of a logistic regression model▪ Provided detailed verbal and written documentation, presentations of modeling techniques and methodologies▪ Delivered actionable insights to the marketing service with non-technical and corporate terms with dashboardso Snapshots of scores: lift, model performance, influence of variables on targeto Snapshots per campaign of discriminating variables and model performanceo Communication channels among the customers with the highest appetite for a product / product to introduce amongst the customers with the highest appetite for a channelo Typology of interactions with the customerso Clustering of zip codes according to scores and discriminating variables▪ Guided need for support and knowledge transfer in a team of 2 members Show less

Corrected Differential Calculus exercices to undergradsElaborated dynamic and interactive teaching strategiesGot several students for individual private tutoring in mathematics : statistics, numerical series and linear algebra

Modelling customer lifetime value of individual customers with Markov Chains :- Helping collecting data from internal databases to create the sample for algorithms - Understand drivers of purchasing behavior to model buying transitions - Cluster customers in homogeneous groups with criterion of generated return with different algorithms ( neural nets, distance based algorithms and probability distribution based clustering algorithms)- validate precision of clustering… Show more Modelling customer lifetime value of individual customers with Markov Chains :- Helping collecting data from internal databases to create the sample for algorithms - Understand drivers of purchasing behavior to model buying transitions - Cluster customers in homogeneous groups with criterion of generated return with different algorithms ( neural nets, distance based algorithms and probability distribution based clustering algorithms)- validate precision of clustering according to return criterion prediction Show less

Statistics Laboratory, Centre de Recherche en Economie et Statistiques (CREST) linked with INSEE (National Institute of Statistics and Economic Studies), Paris — Research Internship, « Study of two comparative approaches: Bayesian clustering and non parametric Bayesian inference based on Dirichlet Process Mixture (DPM) »:- Ensured scientific intelligence regarding non parametric clustering methods based on new research breakthrough- Developed Computational Statistics algorithms… Show more Statistics Laboratory, Centre de Recherche en Economie et Statistiques (CREST) linked with INSEE (National Institute of Statistics and Economic Studies), Paris — Research Internship, « Study of two comparative approaches: Bayesian clustering and non parametric Bayesian inference based on Dirichlet Process Mixture (DPM) »:- Ensured scientific intelligence regarding non parametric clustering methods based on new research breakthrough- Developed Computational Statistics algorithms with Markov Chain Monte Carlo Methods (MCMC) using Matlab Show less

“Crédit du Nord” Bank, retail bank, Société Générale’s Group, in the Company Relationship Management Department, Paris — Assistant Expert in Payment Systems working in close collaboration with the 10 Business Centers of the region Ile de France regarding: assignments about e-commerce and remote transmission of standard transfer bank files for companies: - Monitored EBICS migration in remote transmission: contracts preparation, protocol implementation with technical support… Show more “Crédit du Nord” Bank, retail bank, Société Générale’s Group, in the Company Relationship Management Department, Paris — Assistant Expert in Payment Systems working in close collaboration with the 10 Business Centers of the region Ile de France regarding: assignments about e-commerce and remote transmission of standard transfer bank files for companies: - Monitored EBICS migration in remote transmission: contracts preparation, protocol implementation with technical support, cryptographic signature assets management, customers and network assistance- Advised customers regarding choices of remote transmission products - Supported customer meetings: meeting preparation, diagnosis of customer’s issues- Supported the design of action plans for Business Centers - Prepared and led trainings in Business Centers about remote transmission products Show less