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Lead Data Scientist
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Assessing your cultural and operational fit
Experienced Software Engineer with a demonstrated history of working in the Computer Vision, Machine lEarning industry. Skilled in Python, Android Development, OpenCV, and Computer Vision. Strong engineering professional with a Deep Learning Nanodegree Foundation focused in Computer Science from Udacity.
Aalto University
Master of Science - MS, Data Science
January 1, 2019 – January 1, 2021
Technische Universität Berlin
Master's degree, Data Science
January 1, 2019 – January 1, 2021
Udacity
Deep Learning Nanodegree Foundation, Computer Science
January 1, 2017 – January 1, 2017
Sri Jayachamrajendra ColleCollege of Engineering
Bachelor of Engineering (BE), Computer Science
January 1, 2012 – January 1, 2016
ThreeV Technologies, Inc.
Lead Data Scientist
January 1, 2025 – Present
Remote
Sharper Shape Group
Tech Lead - ML/AI
January 1, 2024 – December 1, 2024
Hybrid
Aalto University Mentoring Programme
Student Mentor
November 1, 2022 – July 1, 2024
Helsinki Metropolitan Area · Remote
Sharper Shape Group
Senior Deep Learning Enginner
September 1, 2021 – December 1, 2023
Hybrid
Aalto University
Thesis Worker
March 1, 2021 – November 1, 2021
Aalto University
Research Assistant
April 1, 2020 – February 1, 2021
Kaaenaat
Machine Learning and Computer Vision Programmer
July 1, 2016 – June 1, 2019
Bengaluru, Karnataka, India
Generate faces
July 1, 2017 – Present
Use generative adversarial networks (GANs) to generate new images of faces.
Translate a Language
May 1, 2017 – June 1, 2017
Building a chatbot that translates text in real time.
Generate TV scripts
April 1, 2017 – Present
Generation of Simpsons TV scripts using RNNs, using part of the Simpsons dataset of scripts from 27 seasons. The Neural Network generates a new TV script for a scene at Moe's Tavern.
Image Classification
March 1, 2017 – Present
Classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. The dataset was preprocessed,and then a convolutional neural network was trained on all the samples.
First neural network
February 1, 2017 – Present
Build and train your own Neural Network from scratch to predict the number of bike-share users on a given day. The data comes from the was used from UCI Machine Learning Database.
Analysis of LiDAR data
December 1, 2016 – June 1, 2017
Automated classification of Aerial & Terrestrial LiDAR & Photogrammetric Data. Accuracy tested across ~4 TB of LiDAR data. Key Responsibilities - Developed a 3-D CNN to classify shapes of objects across 5 classes. - Direction based clustering algorithm written from scratch for classification of power wires accuracy > 95% . - 3 Dimensional and Image based Pattern Recognition algorithms to detect different types of transmission towers - AWS integration and setup for complete automation of processing LiDAR files as they are uploaded to Kaaenaat's servers.
Crop Analysis
July 1, 2016 – October 1, 2016
Crop Analysis Project for over 900 sq km through aerial images. Image Processing & Analysis -Stitching of images and aligning IR and RGB images through feature selection. Agriculture Yield Estimates -Calculation of NDVI and VVI to estimate the crop produce.
Review Rating and Spam Detection
November 1, 2015 – April 1, 2016
Developed an android app to classify reviews as spam and genuine and to rate the reviews of particular products using machine learning.
Real Estate Price Rediction
June 1, 2015 – Present
Developed a java application to predict real estate prices in popular Indian cities using machine learning.
Siblings Recognition
April 1, 2015 – Present
The project was aimed at classifying pair of images as sibling or not. The technology used was based on eigenfaces. The eigenfaces were extracted from the images and the pair was compared using matrices evaluation using MATLAB and classification was done based on the confidence score obtained after evaluation.
Congestion control
March 1, 2015 – Present
Implemented Random early detection algorithm to control congestion in a network of nodes.
Cultural Fit Analysis
The candidate's project diversity, ranging from image classification to LiDAR data analysis and natural language processing, indicates a broad interest and adaptability. The progression through roles from Machine Learning and Computer Vision Programmer to Senior Deep Learning Engineer and then Tech Lead/Lead Data Scientist aligns well with a growth-oriented culture. The involvement in open-source initiatives and mentoring suggests a collaborative and knowledge-sharing mindset. The academic background from multiple international universities also points to an ability to adapt to diverse environments. The target role of ML Engineer is a strong fit for the candidate's demonstrated experience and educational background.
Soft Skills & Operational Fit
The candidate's experience as a Tech Lead and Lead Data Scientist suggests strong leadership, collaboration, and strategic planning skills. Involvement in open-sourcing a dataset (ECLAIR) indicates a proactive and community-oriented approach. The role as a Student Mentor also points to good communication and mentorship abilities. However, without specific psychometric test results, a detailed assessment of logical reasoning, stress handling, and team collaboration is limited.