Antoine M.

Compétences

• scikit-learn4/5
• PyTorch4/5
• TensorFlow3/5
• NLP4/5
• MLflow4/5
• FastAPI4/5
• Docker4/5
• Kubernetes4/5
• CI/CD3/5
• Python4/5
• SQL3/5
• Airflow5/5
• dbt4/5
• AWS5/5
• GCP4/5
• BigQuery5/5
• Databricks5/5
• Terraform4/5
• Deep Learning4/5
• MLOps4/5

Expériences

1. DATA ARCHITECT FREELANCE

   April - June 2026

   • Audited the existing data architecture, reporting workflows and business requirements to identify performance bottlenecks and scalability issues. • Designed a target data architecture and implementation plan to streamline the end-to- end financial reporting pipeline. • Reduced end-to-end processing time from approximately one week to a few hours while improving the development workflow and maintainability of the platform.

2. ANALYTICS ENGINEER FREELANCE

   October 2025 — April 2026

   • Built and maintained the company's analytics stack, covering data ingestion, transformation in BigQuery and delivery of business KPIs through dynamic dashboards. • Integrated new data sources including payment and advertising-spend data to enable user-level acquisition and profitability analysis. • Designed investor-facing dashboards for the company's data room, providing key growth and business metrics during its second fundraising round. • Iterated rapidly on dashboards, metrics and data models as investor and management requirements evolved throughout the fundraising process.

   • BigQuery

3. DATA ENGINEER FREELANCE

   August 2025 — October 2025

   • Built production data pipelines to capture and consolidate student progression data for the rollout of the new 42 curriculum. • Translated academic and operational requirements into business rules used to determine each student's progression through the program. • Implemented data logic to monitor student status and identify whether students were on track or falling behind in their curriculum.

4. DATA SCIENTIST & MLOPS FREELANCE

   July 2023 — March 2024

   • Joined an established Data team as its first Data Scientist / MLOps profile and led the development of a cohort-level player LTV prediction system. • Owned the ML lifecycle end to end, from feature and model experimentation with LightGBM to validation, iteration and production deployment. • Integrated daily LTV predictions into the existing Data Engineering pipelines to power an automated bidder used to optimize user-acquisition campaigns. • Set up Data Science and MLOps project foundations, including reproducible workflows, tooling and engineering practices, while advising the team on additional Data Science use cases.

   • MLOps

5. DATA SCIENTIST & DATA ENGINEER CONSULTANT

   November 2021 — June 2023

   • Developed a methodology to correct incomplete mobile geolocation data by combining observed mobility patterns with Meta demographic data, enabling more representative geographic influence measurements. • Built a recurring geospatial ETL pipeline ingesting Google Maps POIs from keyword-based searches and processing them into a structured data lake. • Developed and productionized an NLP model to automatically categorize restaurant product names, including reproducible model packaging and API deployment. • Developed and improved a restaurant revenue forecasting model with LightGBM and industrialized the prediction workflow through a FastAPI service. • GCP, AWS, BigQuery, PySpark, Airflow, DVC, spaCy, FastAPI, Kubernetes, Docker, Databricks, Delta Live Tables, AWS Lambda, LightGBM, Terraform

   • GCP
   • AWS
   • BigQuery
   • Airflow
   • FastAPI
   • Kubernetes
   • Docker
   • Databricks
   • Terraform
   • NLP

6. DEEP LEARNING ENGINEER

   April - October 2021

   • Ran and analyzed deep-learning experiments to improve the accuracy and quality of the core model generating 3D human animations from 2D videos. • Cleaned, expanded and diversified training datasets and implemented data- augmentation strategies to improve model generalization. • Worked on foot-ground contact modeling to improve the physical consistency and realism of generated 3D animations. • Explored model and architecture improvements based on research papers and evaluated their impact through training experiments.

   • Deep Learning
   • Motion Capture

7. FULL-STACK DEVELOPER

   February - July 2020

   • Maintained and developed an internal back-office application used daily by approximately 150 Customer Care agents. • Delivered full-stack features in Django and VueJS to support evolving customer-service workflows as the business and product offering scaled. • Implemented new pages and business logic supporting a major operational transition from single-box to multi-box customer orders.

   • Django
   • Vue.js

8. DATA SCIENTIST

   June - December 2019

   • Built PySpark pipelines to clean and process several terabytes of historical RFQ data for exotic financial products in the bank's on-premise data lake. • Prepared and analyzed the resulting dataset to support improvements to exotic-product pricing models, including work on underlying volatility interpolation. • Developed a recommendation approach for relevant underlyings aimed at reducing unnecessary Monte Carlo pricing computations and supporting Sales and Pricing teams.