Freelancer profile translated to English.

Description

Data Product Manager specialized in the design, management, and delivery of high-value data and analytics products. I transform business needs into structured, scalable, and KPI-oriented data solutions.

I am involved in the entire product lifecycle: defining the vision and roadmap, prioritizing the backlog, formalizing requirements (user stories), and coordinating multidisciplinary teams (data engineers, BI, IT, business units) in an Agile environment.

Strong expertise in Product Management, KPI design, business intelligence, and data governance, with the ability to transform complex data into actionable indicators for performance management and decision-making.

I support organizations in structuring their data products, improving user adoption, and industrializing their data-driven use cases to generate measurable business impact.

Industry field of expertise

Languages

English
Native or bilingual
French
Native or bilingual
Spanish
Conversational
Arabic
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km), Paris (up to 10km), Nice (up to 10km), Toulouse (up to 10km), Bordeaux (up to 10km)

Eli Lilly & Company
Data & AI Product Manager
MEDICAL
January 2026 - June 2026 (5 months)
Strasbourg, France
Led data & AI initiatives aligned with business and strategic objectives, covering 5 to 8 simultaneous use cases.
Managed and prioritized a structured product backlog representing 30+ data/analytics requests.
Delivered data products and KPI frameworks that improved decision-making and reporting quality, estimated at a +20% business responsiveness.
Coordinated multidisciplinary teams (Data, BI, business units, including 15 active stakeholders) to ensure solution delivery.
Implemented product KPIs (adoption, performance, value) with regular monitoring of 3 to 5 key indicators per product.
Led steering committees and scoping workshops with senior stakeholders/management.
Contributed to the modernization of analytical environments towards cloud architectures, reducing delivery cycles by 30%.
Data Product Management Artificial intelligence Project management Microsoft Power BI
Butachimie
Product Manager Data & Analytics
CHEMICAL
June 2023 - August 2025 (2 years and 2 months)
Chalampé, France
Managed a portfolio of 30+ data & analytics requests from 4 business functions (Production, Quality, Maintenance, Management).
Delivered data products (dashboards, KPIs, reporting) used by 50+ regular active users.
Improved dashboard adoption by +30% through product iteration and user feedback integration.
Reduced operational decision-making time by an estimated -25% through the implementation of automated and centralized KPIs.
Contributed to operational performance gains of +25% by structuring business-oriented data products.
Led over 20 scoping and requirements definition workshops with business and technical teams.
Coordinated Agile delivery with 3 to 6 technical teams (data engineers / BI / IT) in parallel.
Implemented product KPIs and performance monitoring on 10+ critical dashboards.
Product management Product strategy Product Roadmapping & Prioritization Agile methodology Atlassian JIRA
CNRS - Centre national de la recherche scientifique
Data Scientist Engineer
ENERGY AND UTILITIES
December 2022 - June 2023 (6 months)
Clermont-Ferrand, France
- Coordinated with multidisciplinary teams and developed project specifications for the environment division.
- Set up infrastructure, collected, cleaned, modeled, and visualized data.
- Designed, developed, and implemented predictive models and machine learning algorithms.
Deep Learning InfluxDB Random Forest SQL Tableau

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Engineering Degree: Industrial Engineering Option Artificial Intelligence and Data Science
Arts et Métiers National Higher School of Engineering
2022
Machine Learning, Deep Learning, NLP, modèles prédictifs, analyse de données, optimisation de processus, amélioration continue, lean management, Six Sigma, planification de production, simulation industrielle. Python (Pandas, NumPy, scikit-learn, PyTorch, TensorFlow), SQL, BigQuery, Docker, Airflow, Git, Power BI, Tableau, ERP/MES. Cloud : GCP, AWS, Azure. Data Engineering, MLOps, pipelines ETL, maintenance prédictive, optimisation de flux logistiques.

Machine Learning
Coursera
2020
Data collection and analysis Microsoft Power BI Feature Engineering Supervised learning Predictive modeling Unsupervised learning ETL Time series Python

Imane T.

Data & AI Product Manager

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