Aishwarya Srivastava
Data AnalystMachine Learning Engineer
Lacework
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning 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 love working on challenging problems in Computer Science and my ideal role would be one which gives me ample opportunities to do so.
Columbia Engineering
Master's degree, Computer Science
January 1, 2010 – January 1, 2012
National Institute of Technology, Tiruchirappalli
B Tech, Instrumentation
January 1, 2006 – January 1, 2010
P.S.Senior Secondary School
12th Standard, Science (Mathematics, Physics, Chemistry, Computer Science)
January 1, 1994 – January 1, 2006
Lacework
Staff Engineer
May 1, 2023 – Present
Meta
Senior Machine Learning Engineer
November 1, 2017 – January 1, 2023
Menlo Park, California, United States
BloomReach
Member of Technical Staff
August 1, 2014 – October 1, 2017
San Francisco Bay Area
Fino Consulting
Software Engineer
January 1, 2012 – October 1, 2013
New York
Slangwho
Software Engineer Intern
May 1, 2011 – September 1, 2011
New York City Metropolitan Area
Columbia University
Teaching Assistant
January 1, 2011 – December 1, 2011
Goldman Sachs
Summer Analyst, Technology division
May 1, 2009 – June 1, 2009
Predicting the Survival Rate of Passengers on the Titanic
May 1, 2014 – May 1, 2014
• Performed data cleaning on the dataset and selected features of possible importance like age, gender, class of travel etc. • Used Logistic Regression to classify passengers into the “will survive” and “will not survive” categories
Image Compression Using K-Means Clustering
April 1, 2014 – Present
• Compressed a 128 x 128 pixel image by mapping each pixel to a 16-color palette using clustering • Pixels were represented as 3-dimensional points and distance metrics used as the cost function at each successive iteration
Correlation between Education and Abortion Views
March 1, 2014 – Present
• Analyzed the GSS dataset to detect correlation between the educational degree attained and views on abortion • Used the chi-square test of independence to conclude a strong positive correlation at a 99% confidence level
Vehicle Routing Problem
December 1, 2010 – April 1, 2011
Implemented an algorithm for Vehicle Routing Problem with multiple depots and many customers using ant colony optimization techniques
Graph Coloring
May 1, 2008 – June 1, 2008
• Extended existing algorithms for acyclic vertex colouring of graphs with maximum degree 3 to degree 4 and to edge colouring in same degree • Designed an algorithm for the acyclic edge colouring of graphs with maximum degree 4
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Getting and Cleaning Data
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Technology Specialist: .NET Framework 4 Service Communication Applications
Microsoft
June 24, 2026 – Present
R Programming
Coursera
June 24, 2026 – Present
Data Analysis and Statistical Inference
Coursera
June 24, 2026 – Present
VITA/TCE Certification
IRS
June 24, 2026 – Present
Introduction to Finance
Coursera
June 24, 2026 – Present
Professional Developer: Windows Azure Developer
Microsoft
June 24, 2026 – Present
Technology Specialist: .NET Framework 4 Data Access
Microsoft
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic algorithms to practical data analysis and machine learning applications, shows a broad interest in problem-solving. The career progression from Software Engineer to Staff Engineer and Senior Machine Learning Engineer indicates ambition and growth. The target role of 'Data Analyst' is a slight mismatch with the candidate's senior ML/Staff Engineer experience, which is typically more focused on model development and deployment rather than pure analysis. While the candidate has strong analytical skills, the recent roles suggest a more advanced, engineering-focused trajectory.
Soft Skills & Operational Fit
The candidate's experience at Meta and BloomReach suggests an ability to work on complex, impact-driven projects, optimize systems, and collaborate within engineering teams. The teaching assistant role also indicates mentoring and communication skills. However, specific soft skill assessments are not available.