Slayde Ledoux

CONTEXT: Support the Data department in achieving campaign targeting, customer segmentation, and reporting.

STAKEHOLDERS: IT and Reporting Managers.

ROLE: Data Scientist

Model, analyze, and process data.

Harmonize SQL queries developed by Data Analysts and implement best practices for data usage and the Analytics Platform.

Design and maintain data models for Data Analysts, which will support BI systems (dwh, datamarts) or ML algorithms (specific datasets).

Implement indicators and processes for monitoring the quality of the database and relevant business indicator enrichments for developing customer value.

Maintain documentation and definitions of data models accessible to all in our data catalog.

Monitor projects and automate analyses with Python API to Teams.

TECHNICAL ENVIRONMENT: R, Python, SQL, Dataiku.

Research projects within the Investment department to demonstrate the feasibility of a Machine Learning solution aimed at continuously improving the quality of financial instrument data.

- Explore and familiarize with mixed data to perform unsupervised classification (Combination of K-means and HAC).

- Predict the regulatory classification of a financial instrument at the time of data enrichment, and the model will also detect incorrect classifications.

- Implement various Machine Learning models (XGBoost, Random Forest, and Adaboost).

- Present analyses and results. Requires a strong ability to synthesize and simplify technical work, combined with great oral communication skills in front of peers. Technologies used: Dataiku, R, Python, Scikit-Learn.

Data Referent for the R environment:

Lead a project to implement decision-making tools using the R language to best assist business teams.

- Identify R package compatibility issues.

- Implement protocols for setting up R projects.

- Assist with bug fixing.