You're seeing this page as if you were . The main menu is still yours, though. Exit from immersion
Malt Strategy
New report
Malt Tech Trends 2026
Dan SDS

Dan S

Lead AI & GEN AI | Data Scientist | ML Engineer

€700/day
2 projects
Paris, FR
8-15 years
Machine learning
Gen AI
Data science
Développement produit
RAG

Average response time: 1 hour

Freelancer profile translated to English.
Back to original language

About Dan

Expert Data & AI with over 10 years of experience, specializing in the design and deployment of large-scale artificial intelligence solutions. Proficient in various technological stacks and cloud environments (AWS, GCP, Azure), I manage the entire AI project lifecycle, from data collection to model deployment. My added value lies in my ability to translate business needs into high-performing and strategically aligned data, AI, and Gen AI solutions.
Banking and Financial Services
Retail (Small Business)
Consulting and Audits
Luxury Goods
Telecommunications

  • French

    Native or bilingual

  • English

    Fluent

Can work on-site
Paris (up to 50km)

Experience

  • Freelance
    Product Manager / Tech Lead
    CONSULTING AND AUDITS
    January 2025 - October 2025 (9 months)
    Paris, France
    • Design and deployment of an automated evaluation solution for a GenAI model, for product and data science teams.
    • Definition of the target architecture (evaluation pipeline, orchestrator, results storage, monitoring dashboard) in conjunction with tech teams.
    • Implementation of a fine-grained analysis approach for model results: extraction of key metrics, error categorization, relevance scoring.
    • Introduction and implementation of a per-model evaluation method (LLM as a Judge), enabling large-scale benchmarking of multiple model versions.
    • Close collaboration with product, data, and ML teams to integrate evaluation into the model's development and iteration cycles.
    • Contribution to defining internal guidelines on the interpretability and reliability of GenAI models.
    RAG Optimisation Product management Data Engineer Lead data Data visualisation
  • Accenture
    Lead AI & GEN AI
    CONSULTING AND AUDITS
    June 2022 - December 2024 (2 years and 6 months)
    Paris, France
    Data & Generative AI:
    • Leading the adoption and implementation of generative AI models (LLMs) to develop innovative solutions tailored to our clients' needs across various sectors.
    • Transitioning Generative AI POCs to production solutions, addressing the specific challenges of each industry.
    • Adaptation and customization of AI solutions for diverse domains.
    • Implementation of Data solutions: Data Architecture, Data Valorization & AI, DataOps/MLOps, Datalab.
    Experiences:
    • Luxury sector: Implementation of an innovative document management experience via GEN AI.
    • Hospitality sector: Development of a scalable AI based on a FAQ database, currently in production phase.
    • Beauty sector: Conducting workshops for the analysis and synthesis of product creation processes with business and technical teams.
    • Energy sector: Development of the roadmap and strategy for creating a financial datamart, defining objectives and scope of data to be collected and analyzed.
    • Public sector: Design of a global data governance strategy, considering legal, ethical, and operational aspects.
    • Commerce sector: Implementation of a data sharing offering, with guidelines for data quality, confidentiality, and security, as well as a monitoring and adjustment strategy to ensure continuous effectiveness.
    Gen AI ai-and-advanced-analytics Machine learning Product management bi-strategy
  • OnePoint
    Lead Data
    CONSULTING AND AUDITS
    October 2019 - May 2022 (2 years and 7 months)
    Île-de-France, France
    Responsible for the development of Data and AI-based products, from roadmap definition to creation and industrialization. My role involves transforming business needs into robust and scalable data-driven solutions, working closely with technical teams and stakeholders.

    Key Experiences:
    Pass Culture - Data Scientist
    • Design and implementation of efficient data pipelines for optimized collection and processing.
    • Development and deployment of a personalized recommendation algorithm to enhance user experience.
    • Production and industrialization of solutions to ensure their reliability and scalability.

    BPI France - Data & AI Directorate
    • Implementation of the Data Quality Office within BPI France's Data Directorate:
    • Participation in defining the Data Quality policy and structuring the unit's service offerings.
    • Implementation and industrialization of monitoring indicators to ensure rigorous data quality management.
    • Development of Proofs of Concept (POCs) to validate approaches and methodologies.
    • Definition of action scopes, coordination of inter-team contributions, and design of quality controls on various databases.

    EDF - Exploratory NLP Conversation Analysis
    • Exploratory analysis of conversational data using AI technologies to rethink B2C customer journeys.
    • Conducting initial quantitative and qualitative analyses to derive actionable insights.
    • Definition of a reference lexicon to segment and analyze different phases of a customer conversation.
    • Development of models to segment conversations and identify critical steps requiring improvement.
    Product management Data science ai-and-advanced-analytics Google cloud Microsoft Azure
Check out Dan's experience

Reviews

5.0

Out of 2 ratings

S

Samuel

Senior DS - NELAG CONSEIL

Reviewed on 12/12/2025

I worked with Dan on the design and industrialization of a vehicle price prediction model, covering the entire data engineering and data science scope. Dan designed and deployed a data pipeline on Snowflake, from data ingestion and cleaning to advanced feature engineering. Machine learning models were trained, evaluated, and versioned using MLflow, with precise performance tracking. Deployment was carried out on Google Cloud Platform (GCP), with a focus on scalability, MLOps, and industrial production. I particularly appreciated his mastery of data quality issues, data architecture, and industrialization of predictive models. The deliverables were clear, robust, and immediately usable by our teams. I recommend Dan for any predictive modeling, applied data science, or data engineering project involving Snowflake, MLflow, and GCP environments.
R

Raphael

Accompagnement validé pour automatisation via Data - SOSIEGE

Reviewed on 12/3/2025

Dan helped us automate the extraction of information from our invoices using AI and OCR. Result: enormous time savings and much higher reliability than our old manual system. His Gen AI-based solution is easy to use and perfectly suited to our e-commerce business. Dan is professional, clear in his explanations, and very responsive. We recommend him without hesitation.

Recommendations

Judith TaiebJT
Alina GhaniAG
Marc MolodijMM
+1
Judith Taieb and 3 other people have recommended Dan

These freelancer profiles also match your criteria

AgathaA

Agatha Frydrych

Backend Java Software Engineer

4.7

(3)

2

BaptisteB

Baptiste Duhen

Fullstack developer

4.6

(4)

5

AmedA

Amed Hamou

Senior Lead Developer

4

(2)

7

AudreyA

Audrey Champion

Web developer

4.3

(3)

4

Signup to reveal

Education

  • Master 2 (M2), Mathematics Applied To Data science (TIDE)
    Université Paris 1 Panthéon-Sorbonne
    2016
    Master 2 (M2), Mathematics Applied To Data science (TIDE)
  • DATA SCIENCE : DEEP LEARNING, COMPUTER VISION & NLP
    Israel Tech Challenge <itc>
    2019
    DATA SCIENCE : DEEP LEARNING, COMPUTER VISION & NLP
Check out Dan's education

Skill set

Python
Analyse de données
SQL
Big Data
Gestion de projet
Deep Learning
Performance Optimization
AI and Advanced Analytics
Business Intelligence (BI) Strategy
Exploratory Data Analysis
Time Series Analysis and Forecasting
Recommender Systems
Prompt Engineering
RAG Optimisation
Responsible AI
Data visualisation
DBT
Dataiku
Google cloud
Microsoft Azure
Amazon Web Services
AWS
Snowflake
Database Management (e.g., SQL, NoSQL)
ETL (Extract, Transform, Load) Processes
Data Pipelines and Warehousing
Cloud Platforms and Infrastructure
Web scraping
Computer Vision / Image Processing
Model Optimization
Predictive Modeling
Real-time Processing
Model Training and Evaluation
OCR
EXTRACTION DATA

Categories