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Maeva F.MF

Maeva F.

Senior Data Scientist - AI, ML, Bioinformatics

€850/day
Paris, FR
8-15 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Maeva

Bonjour,


Je suis data scientist senior spécialisée en intelligence artificielle, avec une expertise à l’intersection du machine learning, de la biologie et des données complexes.

Vous cherchez à exploiter vos données, développer un modèle prédictif ou tester rapidement une approche en IA (générative, données biologiques, etc.) ? Je vous aide à transformer vos problématiques en solutions concrètes et exploitables.

Ce que je peux vous apporter

  • Modèles ML / deep learning (prédiction, classification)
  • Modèles génératifs (embeddings, diffusion, design de séquences)
  • Analyse de données complexes (biologiques, cliniques, multi-sources)
  • Pipelines data / ML reproductibles
  • Développement rapide de prototypes et d’applications (Streamlit, APIs)

Ma valeur ajoutée

Une triple compétence data science + biologie + ingénierie, avec 5+ ans d’expérience en biotech aux États-Unis (oncologie, thérapies cellulaires).

Je comprends vos enjeux métier et les traduis en modèles réellement utilisables, pas seulement théoriques.

Types de missions

  • Développement de pipelines ML end-to-end
  • Développement rapide de prototypes pour tester une approche IA
  • Analyse bioinformatique (NGS, single-cell, RNA-seq)
  • Outils internes et web apps

Basée à Paris – disponible en remote (temps plein ou partiel).
  • French

    Native or bilingual

  • English

    Native or bilingual

Can work on-site
Paris (up to 10km)

Experience

  • Soufflé Therapeutics
    Director of Data Science and Bioinformatics
    BIOTECH
    January 2024 - Today (2 years and 7 months)
    Watertown, MA, USA
    • • Development of an internal platform for in silico generation of antibody and VHH sequences to accelerate the creation time of a ligand and offer a parallel path to traditional immunization campaigns: selection of protein structure prediction models and generative diffusion models, evaluation of selection metrics, experimental validation of predictions.
    • • Design, training, and deployment of machine learning models to predict siRNA knock-down efficiency from RNA sequence embeddings and biochemical features, reducing the number of candidates to be experimentally tested by 30%.
    • • Implementation of a data infrastructure ensuring the quality, traceability, and reusability of experimental data (FAIR principles) combining databases, Databricks pipelines, and ELN.
    • • Preparation of the data ecosystem for the transition to a clinical regulatory framework (GxP), in collaboration with Quality teams.
    Machine learning Data science Biotechnology
  • 2seventy bio
    Senior Data Scientist
    BIOTECH
    September 2021 - December 2023 (2 years and 3 months)
    Cambridge, MA, USA
    • • Development of machine learning models integrating clinical, CyTOF, NGS, and CMC data to identify factors associated with clinical safety and efficacy in CAR-T trials.
    • • Development of reproducible bioinformatics pipelines for scRNA-seq, bulk RNA-seq, and off-target effect identification of CAR-T therapies.
    • • Development of an automated and generalizable CyTOF analysis pipeline, reducing analysis time from several weeks to a few hours and enabling its use as a clinical trial (R, Nextflow, AWS Batch & Step Functions).
    • • Close collaboration with biostatistics and medical writing teams for result interpretation, preparation of abstracts, and scientific publications.
    • • Contribution to structuring analytical and reproducibility best practices in a regulated context.
  • bluebird bio
    Data Scientist
    BIOTECH
    July 2020 - August 2021 (1 year and 1 month)
    Cambridge, MA, USA
    • • Development of single-cell analysis pipelines for the characterization of therapeutic products, including ATAC-seq and RNA-seq.
    • • Identification of cell populations, clusters, and biological markers of interest for optimizing gene and cell therapy products.
    • • Implementation of reproducible workflows for NGS data analysis in close collaboration with experimental teams.

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Education

  • Doctorate (PhD)
    Stanford University
    2019
    Doctorat (PhD)
  • Master of Science
    Stanford University
    2012
    Master of Science

Skill set

Categories