Ekaterina聽Fedotova
Directora Comercial & Co-founder at ENHO Energy Home
Mexico City
Summary
馃懁
Senior馃帗
Top SchoolEkaterina Fedotova is a business development and partnerships leader with eight years of cross-functional experience scaling operations and commercial strategy in Mexico City. As co-founder and Directora Comercial at ENHO Energy Home, she combines entrepreneurial drive with hands-on project and budget management across startups and multilingual teams. Her background includes multilingual coordination and Chinese鈥揝panish translation in international settings, giving her an edge in cross-cultural negotiations and supplier relations. She has practical project management experience in automotive and education sectors, where she streamlined processes and led teams to meet strategic goals. A contributor to an open-source energy systems project, she has applied data cleaning and back-end scripting skills to map power plant datasets鈥攁n unusual technical complement to her commercial expertise. Ekaterina blends commercial leadership with operational rigor and a rare mix of language, technical, and startup experience.
8 years of coding experience
Bachelor's degree, Chinese Language and Literature, Bachelor's degree, Chinese Language and Literature at Yantai UniversityBachelor's degree, Human Law, B, Bachelor's degree, Human Law, B at RAPERA The Russian Presidential Academy of National Economy and Public Administration
Github Skills (5)
pandas10
geopandas10
data-cleaning10
python10
data-processing10
Programming languages (6)
Github contributions (5)
pypsa-meets-earth/pypsa-earth
Nov 2021 - Jan 2023
PyPSA-Earth: A flexible Python-based open optimisation model to study energy system futures around the world.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 519 reviews, 514 commits in 1 year 2 months
Contributions summary:Ekaterina primarily contributed to the development of the power plant infrastructure, by refining a `build_powerplants.py` script. Their work involved matching the format of custom power plants with the existing powerplantmatching conventions. The changes include refactoring code to utilize pandas-style, renaming columns for better alignment, and mapping different fuel types, technologies and datasets. They also addressed data inconsistencies and performed various data cleaning and validation steps.
power-systemsoptimisation-modelearthpypsa-africasimulation
ekatef/pypsa-eur
Sep 2023 - Sep 2024
PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System
Contributions:34 pushes, 7 branches in 1 year
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