Freelancer profile translated to English.
Back to original languageAbout Okan
AI & Data Engineer with over 5 years of experience in designing and industrializing data solutions with high business impact.
I cover the entire data science project lifecycle: from data ingestion and qualification to cloud deployment in production, including modeling, feature engineering, and the implementation of robust MLOps pipelines.
My main areas of intervention:
- Machine Learning & Scoring— behavioral predictive models (XGBoost, Random Forest, LogReg), AUC/recall optimization, class imbalance management, advanced feature engineering
- MLOps & Industrialization— packaging, CI/CD (GitHub Actions), Docker, MLflow, AWS (EC2, ECR, S3, SageMaker), deployment via FastAPI
- Generative AI & RAG— LangChain pipelines, FAISS/Chroma vector indexing, HuggingFace & OpenAI API integration
- Big Data & Data Engineering— processing massive volumes (+10 billion rows), Vertica/VerticaPy, automated ETL/ELT pipelines
I am involved in both the scoping phase (needs formalization, business KPIs) and the delivery phase (modeling, industrialization, reporting). Comfortable in demanding environments, I am recognized for my ability to communicate with business teams and support the adoption of data tools.
Immediate availability — Rennes/Nantes (2 days remote work) · Paris (min. 3 days remote work)
French
Native or bilingual
Turkish
Native or bilingual
English
Fluent
Spanish
Basic
Can work on-site
Rennes (up to 50km), Nantes (up to 50km), Paris (up to 10km), Angers (up to 50km), Le Mans (up to 50km)
Experience
- Euro Information, Groupe Crédit MutuelData ScientistBANKING AND INSURANCEOctober 2022 - February 2026 (3 years and 4 months)Nantes, FranceMission DescriptionLong-term mission within a leading technology subsidiary, working on large-scale data science and AI projects in a Big Data environment with volumes exceeding 10 billion rows.Key Achievements:
- Development of a 6-month predictive model (LogReg, XGBoost, Random Forest) with advanced feature engineering — rolling averages, weak signals, class imbalance management, AUC/recall optimization
- Large-scale behavioral analysis on +10 billion transactions — multi-criteria segmentation and expense categorization
- Implementation of RAG/LLM pipelines (LangChain, FAISS, HuggingFace) for generative AI use cases in production
- Industrialization of ML models: packaging, automation, CI/CD, Docker/AWS deployment
- Testing and version upgrade of VerticaPy (0.11.x → 1.0.x): unit tests, quality and non-regression checks
- Automation of regulatory reporting via Python/SQL batch pipelines
- Contribution to anomaly detection systems: development and validation of models on suspicious transactions
- Support and assistance for DataLab users (adoption, best practices, business reporting)
Technical Stack:Python SQL VerticaPy Scikit-learn XGBoost LangChain FAISS HuggingFace MLflow Docker AWS CI/CD FastAPI - Banque Populaire Grand OuestData ScientistBANKING AND INSURANCEOctober 2021 - August 2022 (10 months)Rennes, FranceMission DescriptionMission focused on leveraging business data, automating reporting, and implementing analytical strategies for operational and strategic teams.Key Achievements:
- Design and development of Power BI dashboards for operational and strategic management
- Implementation of complex SQL queries — multi-source joins, aggregations, performance optimization
- Implementation of customer targeting strategies: encoding, batch file generation, and campaign monitoring
- Development of analytical indicators for detecting and monitoring at-risk profiles (fraud, incidents, inactivity)
- Automation of reporting and processing — significant reduction in manual tasks
- Close collaboration with business teams for needs formalization and KPI validation
Technical Stack:SQL Power BI Python ETL Automated Reporting - CNP assurancesData ScientistBANKING AND INSURANCESeptember 2020 - September 2021 (1 year)Paris, FranceMission DescriptionMission focused on applied data science, with end-to-end management of a behavioral analysis and predictive modeling project.Key Achievements:
- Complete end-to-end data science project management for behavioral analysis — from data collection to business reporting
- Development of scoring models (retention, inactivity) in Python, R, and SQL
- Actuarial modeling of the impacts of climate change on longevity patterns
- Contribution to the optimization of marketing campaigns through segmentation and predictive analysis
Technical Stack:Python R SQL Scikit-learn Actuarial modeling Segmentation
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Education
- Master in Economic and Financial Engineering, Econometrics and Quantitative EconomicsUniversité de Rennes 12021Master Ingénierie Economique et Financière, Économétrie et économie quantitative
- Bachelor's degree in Economics and Management, Economics and ManagementUniversité de Rennes 12019Licence économie et gestion, Économie et gestion