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Francis OulaFO

Francis Oula

Data Engineer | MLOps | AI (Finance & Data Platfor

€450/day
Paris, FR
3-7 years
Python
SQL
Data Engineering
Machine learning
MLOps

Average response time: 1 hour

Freelancer profile translated to English.
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About Francis

I support you in transforming your financial data into reliable, automated, and actionable decision-making tools.

Specializing in data engineering and artificial intelligence applied to corporate finance (SAP FI/CO type environment), I design robust data pipelines (RAW → SILVER → GOLD) to structure, validate, and enhance your data.

I work on:
• Structuring and industrializing financial data (Python, SQL)
• Implementing business KPIs: cash flow, profitability, cost analysis
• Anomaly detection (fraud, accounting inconsistencies)
• Customer risk scoring (credit management)
• Financial forecasting (cash flow forecast)

I also develop:
• APIs (FastAPI) to expose models
• Management dashboards (Streamlit / BI)
• Reproducible and industrialized environments (Docker, MLOps)

My approach: combining business understanding (finance) with technical expertise to produce concrete solutions, directly usable by teams.

Types of missions:
• Data pipeline implementation
• Financial data analysis and validation
• ML model development (fraud, scoring, forecasting)
• Dashboard and management tool creation
Insurance
Banking and Financial Services
Digital Business Models
Consulting and Audits
Large Retailers

  • French

    Native or bilingual

  • German

    Native or bilingual

  • English

    Fluent

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

Experience

  • Projet personnel / Freelance
    Data Analyst & BI – Financial Analysis
    BANKING AND INSURANCE
    November 2025 - December 2025 (1 month)
    Analysis and structuring of financial data for the production of decision-making indicators with high business value.

    • Cleaning, transformation, and validation of datasets (Python, Pandas, SQL)
    • Design of financial KPIs: profitability, cash flow, cost analysis, and performance
    • Data visualization and reporting (Tableau, Power BI, Streamlit)
    • Exploratory analysis for identifying trends, anomalies, and optimization opportunities

    • Data preparation for scoring models (customer risk) and forecasting (financial forecast)

    Technologies: Python, SQL, Pandas, Tableau, Power BI, Streamlit
    Python SQL Data science Data visualisation Financial Analysis
  • Projet personnel / Freelance
    Data Engineer & AI Engineer – Finance Platform (SAP Simulation)
    BANKING AND INSURANCE
    January 2026 - Today (5 months)
    Paris, France
    Design and implementation of a data & AI platform dedicated to corporate finance (inspired by SAP FI/CO), with the objective of industrializing the exploitation of financial data and improving decision-making (treasury, risk, performance).

    • Design and generation of a realistic dataset integrating accounting entries, cash flows, and credit management data, including anomaly cases (fraud, imbalances, payment delays)

    • Implementation of a complete data pipeline:

    RAW → SILVER → GOLD Architecture
    Data cleaning, structuring, and normalization
    Construction of financial indicators (KPIs): cash flow, cost centers, treasury monitoring

    • Development of Machine Learning models:

    Detection of accounting and financial anomalies
    Customer risk scoring (credit management)
    Cash flow forecasting

    • Production deployment of solutions:

    Deployment of an API (FastAPI) for model exposure
    Development of a management dashboard (Streamlit)
    Complete Dockerization of the architecture (API + dashboard)

    • Design of a financial AI agent:

    Automated financial data analysis
    Generation of business insights
    Decision support

    • Implementation of MLOps practices:

    Code structuring and industrialization
    Reproducible pipeline
    Performance tracking and monitoring

    • Business use cases covered:

    Accounting fraud detection
    Financial imbalance analysis
    Treasury optimization
    Customer risk assessment
    Decision support for financial departments

    Technologies: Python, Pandas, Scikit-learn, FastAPI, Streamlit, Docker

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