About me

 Applied Scientist

Jesus Lago​

I am the lead scientist of a 50-people tech org at Amazon, and the science manager of its ML team. My team and I work on a wide area of topics (e.g. forecasting, ranking, causal inference, A/B testing, or recommendations systems) in order to: i) drive and capturing customer engagement, ii) grow the pool of Amazon customers, and iii) increase the acquisiton of Prime customers.

In addition to my job in forecasting research,  I carry out research and I co-supervise a PhD student in the area of AI and the energy transition, another research topic that I am interested in.

I hold a PhD degree from TU Delft in that same topic, i.e. AI applied to the energy transition, and my PhD research on this domain has received several awards.

I am the developer of optidef, a Latex library for defining optimization problems, and of the epftoolbox python library, the first open-access library for driving research in electricity price forecasting.


2023-Today Amazon
Science Lead & Science Manager

Lead scientist of a 50-people tech team (tech arm of the EU Prime & Marketing org), and science manager of its ML team. My work as a manager requires 50% of my time. The remaining 50% I act as a science lead in multiple projects: i) measuring customer engagement; ii) evaluating impact of Youtube campaigns; iii) recommending discounts to drive customer engagement; iv) evaluating downstream valuation of discounts via causal inference.

2022-2023 Amazon
Senior Applied Scientist

2021 - 2022 Amazon
Applied Scientist

Applied Scientist at Amazon working on forecasting and ranking algorithms.

2016 - 2020 VITO
Research Scientist

Research scientist in AI techniques to facilitate the energy transition and the integration of renewable sources.

2013 - 2016 University of Freiburg
Research and teaching assistant

Research assistant in the area of optimization and optimal control. Teaching assistant in two M.Sc. courses.


2020 TU Delft
Ph.D. - AI for energy systems & markets

PhD in data science in the context of energy systems and energy markets with the end goal of advancing the energy transition through AI.

2016 University of Freiburg
M.Sc. - Microsystems engineering

Masters degree in Microsystems engineering with a major in optimization and optimal control.

2013 University of Vigo
B.Sc.- Electronics, Control and Robotics

Five-year bachelor degree in Electronics, Automatic Control and Robotics


  • IEEE-CIS technical challenge on energy prediction from smart meter data
    Third-place award in the competition of the IEEE-CIS (Computational Intelligence Society) on prediction energy consumption from smart meters.

    Competition | Award

    November 2020

  • Cum Laude in PhD Graduation
    Cum Laude recognition for my PhD research.


    September 2020

  • Applied Energy Highly Cited Paper Award 2020
    Award for one of the most cited papers in Applied Energy in 2020.

    Announcement | Award

    August 2020

  • RTE forecasting competition on French grid load
    Third-place award in an international forecasting competition organized by RTE (the French TSO) where participants had to predict in real-time the day-ahead hourly electricity consumption in France for a period of 14 days.


    April 2018