Raquel Rodriguez
ML EngineerEngineering & Data
Ohalo
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Engineering & Data
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Carnegie Mellon University
Master of Science (MSc), Computer and Information Systems Security/Mobile Systems
January 1, 2015 – January 1, 2017
Universidad de Costa Rica UCR
Bachelor's degree, Computer Science
N/A – Present
Ohalo
Director of Software Engineering
November 1, 2025 – Present
San Francisco Bay Area
Try Your Best
Head of Engineering & Data
April 1, 2023 – October 1, 2025
San Francisco Bay Area
CircleUp
Director of Machine Learning & Analytics
June 1, 2017 – March 1, 2023
San Francisco Bay Area
Procter & Gamble
Software Engineer
March 1, 2013 – May 1, 2015
San Jose, Costa Rica
Cultural Fit Analysis
The candidate has worked in various industries, including biotech (Ohalo), e-commerce/loyalty (Try Your Best), fintech (CircleUp), and consumer goods (Procter & Gamble). This diversity suggests adaptability and an ability to integrate into different organizational cultures. The progression into leadership roles indicates ambition and a drive for impact. The target role of ML Engineer aligns well with the candidate's past experience as Director of Machine Learning & Analytics, though the current role is more focused on general software engineering leadership. The lack of specific project details makes it difficult to fully assess cultural fit beyond role alignment and industry exposure.
Soft Skills & Operational Fit
The candidate's career progression from Software Engineer to Director-level roles in engineering and ML suggests strong leadership, strategic thinking, and operational management skills. Experience in diverse company types (molecular breeding, community rewards, quantitative investing, consumer goods) indicates adaptability and a broad understanding of different business contexts. The descriptions imply a focus on scaling science and managing engineering teams, which requires strong communication, problem-solving, and team collaboration abilities.