Katherine Sanz
Data AnalystStanford MBA Candidate
PepsiCo
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Stanford MBA Candidate
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Stanford University Graduate School of Business
Master of Business Administration - MBA
August 1, 2025 – May 1, 2027
Georgia Institute of Technology
Master of Science - MS, Electrical and Computer Engineering
January 1, 2018 – January 1, 2019
Georgia Institute of Technology
Bachelor of Science - BS, Electrical Engineering
January 1, 2013 – January 1, 2017
PepsiCo
ESG Digitization Manager
September 1, 2023 – August 1, 2025
PepsiCo
Frito Lay Sustainability Digitization Lead
February 1, 2022 – September 1, 2023
PepsiCo
Senior Electrical Engineer - Sustainability
April 1, 2020 – February 1, 2022
The Chemours Company
Sustainability Consultant
May 1, 2019 – April 1, 2020
Hybrid
ExxonMobil
Instrumention and PLC Engineer
May 1, 2018 – August 1, 2018
Baytown, Texas, United States
Georgia Tech Research Institute
Machine Learning Researcher
May 1, 2017 – December 1, 2019
Atlanta, Georgia, United States
Texas Instruments
Product Marketing Engineering
May 1, 2016 – August 1, 2016
Santa Clara, California, United States
General Motors
Vehicle Performance Energy Integration
August 1, 2015 – December 1, 2015
Milford, Michigan, United States
General Motors
Vehicle Development Validation
May 1, 2014 – August 1, 2014
Milford, Michigan, United States
Algenol Feasibility Study of a Filamentous Algae Producing Facility
January 1, 2018 – May 1, 2018
• Explored the economic and sustainable feasibility of a filamentous algae producing facility by exploring the areas of aeration and agitation, dewatering, drying, and carbon offset. • Investigated, modeled, and simulated different methods of dewatering and drying. Determined energy footprints associated with different practices, and outlined differences between single celled and filamentous cyanobacteria. • Determined the environmental impact of displacing nitrogen fertilizers with an algal fertilizer and the associated GHG footprint of the displaced material.
Sustainable Aquaponic System
January 1, 2017 – May 1, 2017
• Conducted research in Aquaponic technologies in order to create an efficient food-energy-water system in urban areas where the water and nutrients can be recycled in as many closed loops. • Built prototype of greenhouse aquaponic farm that was nearly net-zero in energy, water and materials by using photovoltaics, solar water heating, rainwater capture, algal/zooplankton [used for the fish feed], and food waste as fertilizer. • Created photovoltaic system and specifications to power aquaponic system, and designed mounting system for solar panels.
Cultural Fit Analysis
The candidate's background is heavily skewed towards engineering, sustainability, and project management, with a strong academic foundation. While the projects demonstrate analytical skills, there is a lack of explicit data analysis tools or methodologies mentioned that directly align with a typical Data Analyst role. The upcoming MBA suggests a career trajectory towards business leadership rather than a deep technical data analysis specialization. The diverse experience across different industries (manufacturing, research, consumer goods) indicates adaptability, but the direct cultural fit for a dedicated Data Analyst role, especially in a tech-focused environment, is not strongly evident from the provided data.
Soft Skills & Operational Fit
The candidate's project descriptions suggest strong analytical thinking, problem-solving, and research capabilities. Their career progression at PepsiCo from Senior Electrical Engineer to ESG Digitization Manager indicates leadership potential and an ability to manage complex initiatives. The focus on sustainability and efficiency aligns with operational roles requiring data-driven decision-making.