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Ferran A.FA

Ferran A.

Senior Data Scientist | ML & AI | Data Analytics

€500/day
Sofia, BG
15+ years

Average response time: 1 hour

About Ferran

For over a decade, my professional journey has been dedicated to uncovering the story hidden within data. I began with a foundation in actuarial science and have since progressed into senior data science roles where I specialize in translating complex patterns into measurable business value.

As a Senior Data Scientist, I thrive on tackling end-to-end challenges. My job isn't just about building models; it's about understanding the business problem deeply, architecting a scalable solution, and ensuring it drives real-world impact.

My technical approach is comprehensive and grounded in robust engineering. This involves architecting and implementing scalable data pipelines using PySpark within the Microsoft Azure and Databricks ecosystem, ensuring solutions are not only effective but also efficient and maintainable through MLOps practices. A significant area of my current work is focused on the practical application of Large Language Models (LLMs), where I develop custom RAG frameworks to unlock new capabilities from complex data. Throughout all projects, I emphasize clear communication, translating analytical findings into strategic recommendations for leadership.

Beyond my corporate responsibilities, I am committed to advancing the field by mentoring the next generation of talent. As a Part-time Lecturer for the University of Barcelona's Master in Big Data & Data Science, I teach advanced data mining techniques, helping to bridge the gap between academic theory and real-world industry application.

This passion for the field extends beyond the office and the classroom. When I'm not working, you'll often find me exploring the latest breakthroughs in Generative AI, diving into new research papers on statistics and machine learning, or simply experimenting with emerging AI architectures. For me, data science isn't just a profession, it's a field of endless discovery.
  • English

    Fluent

  • Spanish

    Native or bilingual

  • Catalan

    Native or bilingual

Remote only
Primarily works remotely

Experience

  • Avolta AG - Dufry (CH)
    Senior Data Scientst
    RETAIL (LARGE RETAILERS)
    September 2022 - Today (3 years and 11 months)
    As a member of Global Data & AI Team, my key responsibilities included:

    ✔ Providing in-depth analytical support and conducting quantitative analysis for Assortment Optimization, Basket Analysis and Performance Analyzer initiatives. This involves tasks such as Store Clustering, performing multidimensional Descriptive Analysis of results, collecting the most relevant insights creating meaningful KPIs, and addressing complex optimization problems.

    ✔ Maintenance and enhancement of critical data visualization dashboards used for business analysis and active monitoring of most relevant KPIs.

    ✔ Actively involved in the implementation and application of Large Language Models (LLMs) using the LangChain framework in order to build a custom RAG framework.

    ✔ Python and R for data analysis, statistical modeling, mathematical reasoning.

    ✔ PySpark for the development of analytical pipelines, scaling and productionizing Machine Learning models and data processing tasks on large datasets.

    ✔ Working extensively with the Databricks platform within the Microsoft Azure cloud environment for collaborative data processing, model development, and deployment.
    Python Databricks MLOps Agile method SQL
  • Universitat de Barcelona
    University Lecturer
    EDUCATION AND E-LEARNING
    March 2021 - Today (5 years and 5 months)
    My role focuses on bridging the gap between complex academic theory and its practical application in a real-world business context. I am in charge of the "Advanced Data Mining Techniques" module, instructing a graduate students and experienced professionals on how to get actionable insights from complex datasets.

    Key Topics & Responsibilities:

    ✔ Advanced Statistical Modeling: Multivariate analysis and Hypothesis Testing to build robust statistical arguments.

    ✔ Unsupervised Learning: Dimensionality reduction with Principal Component Analysis (PCA), Factorial Analysis and Clustering algorithms.

    ✔ Predictive Classification: Application of discriminant analysis for building effective classification models.

    ✔ Foundational Theory: Reinforcing the core principles of probability distributions and the Central Limit Theorem.

    ✔Practical Application: Fostering a hands-on learning environment where students apply these techniques to industry-relevant case studies, preparing them for the challenges of a data science career.
    R Business analysis E-learning AI Automation Data mining
  • AXA
    Senior Data Scientst
    BANKING AND INSURANCE
    September 2016 - September 2022 (6 years)
    As a member of Global Data Team, my key responsibilities included:

    ✔ Led the end-to-end design, development, implementation, and maintenance of core business predictive models, including Market Forecasting, Customer Churn Prediction, and Cross-Selling optimization, driving data-driven strategies across the company.

    ✔ Developed and maintained interactive data visualization dashboards to monitor key business performance indicators (KPIs), track model performance, and communicate complex analytical findings to stakeholders across different departments.

    ✔ Implementing Machine Learning algorithms in data workflows to address complex business problems and extract actionable insights from large datasets.

    ✔ Leveraged expertise in Python and R for data manipulation, statistical analysis, model development, and automation of analytical workflows.

    ✔ Engineered and deployed data pipelines and analytical solutions within the Microsoft Azure cloud environment (Azure Databricks) for efficient processing and analysis of large-scale datasets.
    Data analysis Azure DevOps Data Engineer Data science Big Data

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Education

  • Microsoft Professional Program on Data Science
    Microsoft Academy
    2016
    Comprehensive program of 9 practical courses covering core Data Science topics. Course topics included: - Data Science Essentials - Querying Data with Transact-SQL - Analyzing and Visualizing Data with PowerBI - Statistical Thinking for Data Science and Analytics - Introduction to R and Python for Data Science - Programming with R and Python for Data Science - Data Science Essentials - Machine Learning Essentials - Applied Machine Learning - Data Science Challenge
  • Master's Degree in Data Science and Machine Learning
    MBIT School
    2016
    Intensive Executive Master's program providing a deep dive into the core principles, methodologies, and technologies essential for successful Data Science practice.

Skill set

Categories