Andrea Klein
Data AnalystDirector of Engineering, AI Infrastructure
Arm
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Director of Engineering, AI Infrastructure
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 (MS), Computer Science
January 1, 2012 – January 1, 2013
Stanford University
Bachelor of Science (BS), Physics (with honors)
January 1, 2008 – January 1, 2012
Arm
Director of Engineering, AI Infrastructure
May 1, 2025 – Present
Apple
Senior Engineering Manager
October 1, 2021 – May 1, 2025
Apple
Principal Machine Learning Engineer, Tech Lead Manager
September 1, 2021 – October 1, 2021
Apple
Staff Machine Learning Engineer, Tech Lead Manager
September 1, 2019 – August 1, 2021
Apple
Senior Machine Learning Engineer
October 1, 2017 – September 1, 2019
Apple
Machine Learning Engineer
April 1, 2017 – September 1, 2017
Apple
Machine Learning Engineer
March 1, 2016 – April 1, 2017
Software Engineer
April 1, 2014 – March 1, 2016
Mountain View, California
Carnegie Mellon University
Teaching Assistant (Computer Science)
August 1, 2013 – December 1, 2013
Venmo
Data Science Consultant
August 1, 2013 – October 1, 2013
Venmo
Data Science Intern
May 1, 2013 – August 1, 2013
Venmo
Data Science Consultant
January 1, 2013 – May 1, 2013
Carnegie Mellon University
Researcher
January 1, 2013 – May 1, 2013
SLAC National Accelerator Laboratory
Summer Student, Research Support
June 1, 2012 – August 1, 2012
Stanford University
Teaching Assistant (Physics)
January 1, 2012 – April 1, 2012
Stanford University
Undergraduate Honors Thesis Research
September 1, 2011 – June 1, 2012
Stanford University
Teaching Assistant (Physics)
September 1, 2011 – December 1, 2011
SLAC National Accelerator Laboratory
Undergraduate Researcher
June 1, 2011 – September 1, 2011
Zenith Tutoring
Private Tutor
January 1, 2010 – June 1, 2012
Fermilab
Undergraduate Researcher
July 1, 2009 – September 1, 2009
Scaling up L1 regularized logistic regression
March 1, 2013 – May 1, 2013
Combined previous works in the field to develop a simple yet highly scalable (parallelizable) and efficient algorithm for fitting L1 regularized logistic regression models to very large datasets. The algorithm used Iteratively Reweighted Least Squares-Least Angle Regression (IRLS-LARS) as the primary learner. The technique is not only faster, but in fact is empirically seen to generalize better than the original non-parallelized model.
Cultural Fit Analysis
The candidate's diverse experience across research, software engineering (SRE), and machine learning engineering, coupled with leadership roles, indicates adaptability and a broad technical perspective. Their academic background in physics and computer science, along with research in cosmology and machine learning, suggests a strong foundation in quantitative analysis and complex problem-solving. The progression through various roles at Apple, from Machine Learning Engineer to Senior Engineering Manager, demonstrates a commitment to growth and impact within large organizations. The target role of 'Data Analyst' seems significantly junior to their current and past leadership positions, which might indicate a potential mismatch in expectations or a desire for a career pivot. The candidate's profile suggests a strong fit for roles requiring deep technical expertise, leadership, and strategic thinking in data-intensive environments.
Soft Skills & Operational Fit
The candidate's career progression from individual contributor to senior management roles at major tech companies suggests strong leadership, problem-solving, and strategic thinking abilities. Their involvement in teaching and research indicates a capacity for knowledge transfer and continuous learning. The detailed descriptions of projects and roles, particularly at Venmo, highlight analytical rigor and practical application of data science concepts. However, without specific psychometric test results, a direct assessment of work attitude, stress handling, and team collaboration is limited.