Mayank Gupta
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Product Quality@Etched | Ex-Apple | Building 108Journeys
I’m a Product Quality Manager at Apple, where I work at the intersection of engineering, manufacturing, and execution to deliver reliable, high-quality products at scale. My experience spans end to end product quality starting from development and supplier readiness to mass production and continuous improvement In parallel, I’m the co-founder of 108Journeys, a mindful travel and retreat company curating immersive yoga, meditation, and spiritual journeys rooted in cultural heritage and conscious exploration. Across both roles, I’m motivated by the same principles: building thoughtful systems, maintaining high standards, and creating experiences that people trust—whether that’s a consumer product used by millions or a journey that impacts lives in a more personal way.
Purdue University
Master of Science (MS), Industrial Engineering
January 1, 2016 – May 1, 2018
Indian Institute of Technology (Indian School of Mines), Dhanbad
Bachelor of Technology (B.Tech.), Mining Machinery
January 1, 2010 – January 1, 2014
Etched
Member of Technical Staff
April 1, 2026 – Present
On-site
108Journeys
Co-Founder
January 1, 2026 – Present
San Francisco Bay Area
The Posse Foundation
Career Coach
January 1, 2025 – July 1, 2025
Remote
Apple
Product Quality Manager
February 1, 2019 – April 1, 2026
Cupertino, CA
Apple
Data Science Intern- iPhone Operations
April 1, 2018 – August 1, 2018
Apple
Data Science Intern- Manufacturing Design
January 1, 2018 – April 1, 2018
Purdue University
Graduate Research Assistant
September 1, 2016 – December 1, 2017
West Lafayette, Indiana
Building Construction Products, Caterpillar Inc.
Manufacturing Engineer
February 1, 2015 – July 1, 2015
Chennai
Product Development & Global Technology, Caterpillar Inc
Design Engineer
July 1, 2014 – May 1, 2016
Chennai
Tata Steel
Engineering Intern
May 1, 2013 – July 1, 2013
Jharia
Predicting health parameters from a camera based video using Machine Learning and Computer Vision
May 1, 2017 – December 1, 2017
The motivation of this project is the advancement in the use of non-contact devices (camera based video) instead of contact devices (ECG machine, pulse oximetry) and invasive techniques to measure the basic health parameters like pulse rate, blood pressure, and oxygen saturation level in blood. We recorded the video of the person to predict the heart beat. The first step involves the detection and alignment of the person's face from the video. This is achieved using the algorithm named DeepFace which has been developed by Facebook. The face features are extracted from the face and have been filtered using a band-pass filter to remove the surrounding noise from the image. These face features are trained using the actual data (PPG signal) from pulse oximetry device using machine learning algorithm. The trained model will be used to predict the PPG signal of different people using their video. This work is in progress and will be extended to predict oxygen saturation level in blood, stress level in the person and the arterial stiffness of a person.
Time Series Analysis of US immigration data
March 1, 2017 – April 1, 2017
-> Collected the data on annual immigration into the U.S. from 1820 to 1962 ->Adopted time series modelling techniques to come up with the best model that explains the phenomenon -> Analysis of autocorrelation function (acf) and partial autocorrelation function (pacf) to understand the best model -> Used various ARIMA(p,d,q) models by varying the order and chose the best model based on the significance of parameters and the residual analysis
Data Driven predictive analysis of pavement performance
January 1, 2017 – May 1, 2017
• Prediction of pavement roughness index using data from large repository of data collected over two decades • Assess the effect of loading, environment, material properties, construction quality, & maintenance level on pavement performance using methods of supervised learning
Tuning-free Distributed Algorithm for Nonconvex Big-Data Analytics
October 1, 2016 – November 1, 2016
Studied the optimization algorithm used in multiagent distributed system and modified it with uncoordinated step size Performed the simulations on sparse regression problem and achieved better consensus results
Facial Recognition using Principal Component Analysis
September 1, 2016 – November 1, 2016
The aim was to train the system with a bunch of train images and build a system which can recognize the facial features of the people Used the concept of Principal Component Analysis while training the system by projecting the feature space the lower dimension using singular value decomposition Tested the images from the test set using different eigen faces every time
Techno-Economic Assessment (TEA) of value recovery opportunities from End-of-Life Products
September 1, 2016 – December 1, 2017
(Department of Energy, U.S. funded research project) Developing generic TEA model that will act as a decision-making tool for assessing emerging technologies Performed cost, benefit & risk assessment for bioleaching Rare Earth Elements from the stream of waste products
Prediction of Housing Prices in Iowa by pointing out the significant variables that impact the price trend using Linear Regression Analysis
August 1, 2016 – December 1, 2016
-The raw data of housing prices and predictors like area, parking area,location,number of floors, etc. was analysed using Linear Regression -The aim was to select at the most useful variables that best explains the housing price statistically. - The 4 assumptions of linear regression model are checked namely: linearity, normality, constant variance and independence using scatter plots, residual plots, QQ plots and sequence plot and if needed, variables are transformed accordingly - Choosing best subset of predictors which best explains the relation between predictors and response variable using Mallow's Cp criterion, AIC, BIC, Adjusted R-square. - Performed weighted regression to make the variance constant. - The outliers and influential points are detected using studentized deleted residuals, hat matrix diagonals and Cook's distance.
Intro to Python for Data Science
DataCamp
June 24, 2026 – Present
Foundation Course on CATIA
CADD Center, Kanpur
June 24, 2026 – Present
Fundamentals of Quantitative Modeling
Coursera
June 24, 2026 – Present
Engineering Rotational Development Program
Caterpillar Inc.
June 24, 2026 – Present
Applied Statistics and Probability
Indian Institute of Technology, Madras
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from academic research to practical applications in manufacturing and product quality, suggests adaptability and a broad interest in problem-solving. The transition from engineering to data science, and then to product quality management, indicates a willingness to learn and adapt. The co-founder role also shows initiative. However, the recent career shift towards non-technical roles (Co-Founder, Career Coach) might require clarification regarding long-term commitment to a Data Analyst role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a methodical approach to problem-solving and a strong analytical mindset. Experience at Apple and Caterpillar suggests an ability to operate in structured, high-quality environments. The co-founder role at 108Journeys, while not directly technical, hints at entrepreneurial drive and leadership potential.