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Distinguished Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I am a Tech Lead, Director of Engineering, at Facebook driving cross-functional initiatives to enable new lines of business powered by state-of-the-art AI.
Stony Brook University
Ph.D., Elementary Particle Physics
January 1, 2004 – January 1, 2009
The Johns Hopkins University
Bachelors Degree, Physics, Computer Science
January 1, 2000 – January 1, 2004
Distinguished Engineer, Neural Interfaces
June 1, 2022 – Present
Director Of Engineering, Business Integrity
April 1, 2017 – June 1, 2022
Machine Learning Engineer, Business Integrity
December 1, 2014 – April 1, 2017
AT&T Big Data
Associate Director of Data Insights
October 1, 2014 – December 1, 2014
Palo Alto, CA
AT&T Big Data
Senior Data Scientist
December 1, 2013 – October 1, 2014
Palo Alto, CA
CERN
User
January 1, 2010 – November 1, 2012
Geneva, Switzerland
Stanford / SLAC National Accelerator Laboratory
Research Associate
September 1, 2009 – December 1, 2013
Palo Alto, CA
Fermilab
User
January 1, 2006 – August 1, 2009
Batavia, IL
Stony Brook University
Graduate Student
September 1, 2004 – August 1, 2009
Stonybrook, NY
Kaggle Data Science Competitions
January 1, 2013 – Present
Ranked 321st out of 114,957 amateur and professional data scientists using a mix of data mining techniques, machine learning algorithms, and old-fashioned detective work: ● Digit Recognizer -- currently in the top 5%, using an SVM and computer vision techniques. ● KDD Cup 2013 - Author-Paper Identification Challenge (Track 1) -- placed in the top 10%, generating features with SQL and performing classification with boosted decision trees. ● Cause-effect pairs -- placed in the top 10%, fitting trends using neural networks, quantifying distributions using statistical methods, and classification with random forests. ● Amazon.com Employee Access Challenge -- placed in the top 25%, using a k-means clustering algorithm and a logistic regression.
Cultural Fit Analysis
The candidate's diverse background, spanning fundamental physics research (CERN, Stanford, Fermilab), large-scale data science at AT&T, and senior leadership in AI/ML at Facebook, demonstrates adaptability and a broad intellectual curiosity. Their engagement in Kaggle competitions and academic research indicates a continuous learning mindset and a passion for complex problem-solving. The progression from individual contributor to distinguished engineer and director roles, coupled with experience in integrity and privacy, suggests a strong ethical compass and a commitment to responsible technology development. This profile aligns well with a culture that values innovation, technical depth, and impactful contributions.
Soft Skills & Operational Fit
The candidate's experience at Facebook as a Distinguished Engineer and Director of Engineering, along with their roles at CERN and Stanford, indicates strong leadership, project management, and cross-functional collaboration skills. Their ability to define technical strategy, own end-to-end quality, and make critical trade-offs suggests excellent operational fit. The description of managing teams and driving initiatives across 100+ engineers highlights strong communication and organizational capabilities. Their involvement in Kaggle competitions also points to a self-driven and competitive nature.