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Malt Strategy
Antonio S.AS

Antonio S.

Lead data scientist

€450/day
Madrid, ES
3-7 years
Python
Predictive Maintenance
Consulting
Generative AI
Cloud computing

Average response time: 1 hour

About Antonio

Data scientist with a background in Big Data, AI, and Deep Learning. I have developed analytical solutions for sectors such as energy, industry, and finance, leading projects in predictive maintenance, GenAI-based automation, and financial risk classification for major international companies. My range of professional skills includes predictive modeling (XGBoost, neural networks), cloud pipeline development (BigQuery, Azure, Airflow), and advanced data analysis. I also actively contribute to data strategy design and technical proposals for clients.
Consulting and Audits

  • Spanish

    Native or bilingual

  • English

    Fluent

Remote only
Primarily works remotely

Experience

  • Quantrue
    Senior data scientist
    September 2023 - Today (2 years and 9 months)
    Key Responsibilities & Projects:

    • Automation of Supplier Quotation Processing (GenAI)
    Designed and implemented a solution to automate the ingestion and reconciliation of supplier quotations. Built a pipeline using LangChain and generative AI to extract unstructured data from emails. Reduced manual workload by ~1.5 hours per user/day.
    Technologies: Python (LangChain, OpenAI), email tools, GitHub.

    • Invoice Payment Delay Classification
    Led the development of a multiclass prediction model to categorize invoice delays (on-time, delayed, heavily delayed). Integrated a creditworthiness scoring system to support strategic decisions. Managed a team of 3 data scientists. Deployed on Google Cloud.
    Technologies: Python (XGBoost), BigQuery, Airflow, GitHub.

    • Predictive Maintenance – Industrial IoT
    Developed deep learning models for predictive maintenance of industrial equipment using sensor data, detecting over 20% of failures in advance. Acted as main client-facing lead, including on-site presentations.
    Led phase two, expanding models to new components. Managed a team of 4, delivering 4 new models with ~20% gain in failure detection.
    Technologies: Python (PyTorch, scikit-learn), PySpark, Azure (Synapse, AzureML), GitHub.

    • Additional Contributions
    Supported recruitment, conducted interviews, and contributed to international pre-sales. Participated in internal demo development for GenAI, optimization, and related use cases.
  • NTT Spain
    Senior data scientist
    TELECOMMUNICATIONS
    July 2023 - September 2023 (2 months)
    Key Responsibilities & Projects:

    • Customer Churn & Demand Forecasting – Energy Sector
    Redesigned an outdated customer churn prediction model for energy and gas contracts, scoring ~7 million contracts monthly. Achieved a 2x improvement in predictive performance.
    Built ARIMA-based time series models to forecast call center and in-store traffic, achieving a MAPE below 10%.

    • Commodity Price Forecasting – Renewable Energy Industry
    Developed and deployed ML models to forecast key commodity prices, enabling better procurement strategies for equipment linked to metals markets. Created a dashboard for results monitoring. Mentored two junior team members and regularly engaged with stakeholders.

    • Electricity Price Prediction – Internal R&D Project
    Built time series and regression models to forecast intraday power spot prices. Significantly improved ETL performance, reducing computation time by 90%. Delivered accurate forecasting outputs for internal decision-making.

    • Advanced Analytics Strategy – Telecommunications Industry
    Assessed customer service operations to identify areas of improvement. Proposed six high-impact use cases for analytics implementation, aligned with business priorities.

    • Consulting & Pre-Sales Support
    Contributed to data science proposals and client pitches. Co-developed a Marketing Mix Modeling (MMM) framework and accelerator, reducing project delivery time by ~3 weeks.

    Main Technologies: Python (Pandas, NumPy, scikit-learn, XGBoost), R (Tidyverse, Plotly, ClusterR, Shiny), GitHub, Azure Cloud (VM, AKS), Office tools.
  • Deloitte
    Risk quantitative analyst. Advisory Banking
    May 2021 - October 2021 (5 months)
    Main responsibilities & projects:

    Development and maintenance of credit risk models for a major financial institution.
    Assisted in modeling the loss given default (LGD) parameter under the IFRS9 standard. Conducted data analysis and generated insights on customer data, preparing impact reports to support decision making based on model outcomes.
    Main technologies used: SAS (SQL), Python (Pandas & NumPy), and Microsoft Office suite.

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Education

  • Postgraduate in artificial intelligence and deep learning.
    Technical University of Catalonia (UPC).
    2023
    Postgraduate in artificial intelligence and deep learning.
  • Master's degree in Big Data & Business Analytics.
    School of Industrial Organization (EOI).
    2021
    Master's degree in Big Data & Business Analytics.
Check out Antonio's education

Skill set

Chatbot IA
Azure DevOps
Google Cloud Platform (GCP)

Categories