Freelancer profile translated to English.
Back to original languageAbout Sophie
Senior statistician with over 20 years of experience at INSEE in complex data analysis, with a double background in data science (recent master's degree) and social sciences (research master's degree). First co-author of a scientific communication (ERIC Lyon 2, LIRIS CNRS) presented at INSEE's JMS 2025 on deep learning graph analysis.
Producing numbers is easy.
Understanding what they actually measure is much less so.
My role: intervening when data exists but indicators are questionable, their limitations poorly identified, and decision-making difficult. I help formulate analyses and models that are truly usable for decision-making.
Framing and reformulating statistical and data problems
(vague objectives, questionable indicators, metrics disconnected from decision-making)
Robust statistical analyses
(descriptive, inferential, reasoned segmentation, indicators)
Data science and modeling adapted to the context
(when relevant, and only when it is)
Sociological analysis of data, uses, and markets
(understanding populations, collection biases, exclusion effects)
Qualitative contributions in social sciences
(semi-structured interviews, narrative analysis, contextualization of data)
Targeted expertise and bibliographic research
to shed light on poorly understood markets, products, or populations
Philippe Manipoud (CEO, Alberture)
« [Sophie] quickly distinguished herself with her ability to deeply analyze complex data, mobilizing her skills in sociology, statistics, and data science. Her strength also lies in her ability to present her results clearly, structured, and concisely, making her deliverables immediately usable. Sophie brought real added value to our strategic thinking. »
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👉 All my recommendations are on LinkedIn: linkedin.com/in/sophie-perrin-statisticienne
French
Native or bilingual
English
Fluent
German
Conversational
Spanish
Fluent
Icelandic
Basic
Can work on-site
Lyon (up to 10km)
Experience
- AlbertureData scientist R&D – anomaly detection on graphs and sociology of banking inclusionTECHMarch 2025 - July 2025 (4 months)Givors, FranceR&D project in data science applied to human and social sciences, resulting in a scientific communication presented at the INSEE's Statistical Methodology Days (JMS) 2025, in collaboration with CNRS (LIRIS – Université Lyon 1) and the ERIC laboratory (Université Lyon 2). Supervised by Cyril Perosino (CIFRE PhD student at a deep tech startup) - project carried out as part of my master's thesis.Methodological, technical, and interpretative contributions, as well as pedagogical and commercial valorization of results to non-technical audiences.My contributions👉Modeling and R&D:* Contribution to the design of a graph anomaly detection model (GNN), in supervised and semi-supervised learning.* Comparative study of hierarchical clustering methods in hyperbolic geometry (HypHC) and spectral clustering, to improve model performance.* Proposal of data from human and social sciences relevant to enrich the model's inputs.* Consideration of the regulatory framework for a model classified as "high risk" by the AI Act.👉Valorization, pedagogy, and communication:* Co-authoring of pedagogical and commercial materials, translating complex mathematical concepts (fairness, explainability, clustering, graph anomaly detection) into clear and differentiating messages for non-technical stakeholders.* Design, based on an economics thesis, of a summary slideshow (65 slides), as well as a summary and an executive summary for communication and decision-making purposes.Organization and toolsMultidisciplinary teamwork (data science, HSS, marketing)Development in Python, use of collaborative tools (Git, Jupyter, VS Code)
- inseeSenior statistician – public data analysis, surveys, and data qualityPUBLIC SECTOROctober 2003 - Today (22 years and 8 months)Lyon, FranceIntervention on methodological and statistical analysis issues, ensuring thedecision-making use of resultsand their **understanding by non-specialist audiences**.
Skills used:
Statistical Analysis- Analysis of survey data, including **very large volumes**.
- Evaluation ofdata quality(non-response, bias, structural effects, collection methods).
- Construction ofindicatorsandtypologiesfor decision support.
Programming- Data processing in **R, SQL, SAS**.
Transmission and valorization- Writingstatistical publicationsand **analysis notes**.
- Presentation of results to **institutional**, **professional**, and **media audiences**.
- Explanation ofmethods used in constrained contexts(e.g., health crisis).
Examples of achievements:
National analysis of theeffects of interview-based collectionon the quality of population census data.Writing ofregional statistical studies(Auvergne-Rhône-Alpes), publicly disseminated, andpresentationof these analyses **at press conferences**.Creation of a typology of non-responding establishments in the tourism survey, allowing for **effective targeting of follow-ups**.Analysis, **combining qualitative sociological interviews and statistical analysis**, of the causes of persistent non-response from certain establishments in the monthly hotel occupancy survey, to improve data collection.Study on non-salaried workers:innovativeexploitation of a **complex administrative database**, **inter-regional technical coordination**, creation of shared SAS scripts and a variable dictionary. - Compagnons du Devoir ; éducation nationaleMathematics teacherEDUCATION AND E-LEARNINGSeptember 1999 - June 2002 (2 years and 10 months)Lyon, FranceItaughta wide variety of audiences:middle schoolers**, **high schoolers**, and **young adults in manual trades(evening classes after physically demanding workdays for them).These experiences taught me tostructure clear explanations**, to **effectively simplify complex concepts**, and to **maintain attentioneven in contexts not conducive to concentration.
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Education
- Master 2 MIASHS (Mathematics and Computer Science Applied to Human and Social Sciences)Université Lyon 22025Mention bien (après accès direct sans avoir fait de master 1) Contenu : data science - machine learning - deep learning - analyse de réseaux Communication "Combiner clustering hiérarchique et spectral pour la détection d'anomalies dans des graphes : application aux réseaux sociaux" présentée aux Journées de la Méthodologie Statistique (JMS) de l'INSEE 2025
- Research Master's Degree - Social and Cultural AnthropologyUniversité Lyon 22010Mention très bien (après accès direct au niveau Licence 3) Mémoire de recherche "L'inceste : consistance du silence - France, 20 et 21e siècles" lauréat du 2e prix scientifique de la CNAF (Caisse Nationale des Allocations Familiales)