Manjari Akella
Data AnalystSenior Software Engineer at Uber
Uber
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior Software Engineer at Uber
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
- 9+ years industry experience - 7+ years experience with Golang - Backend Platform engineering - Experience with Monorepos - Passionate about mentoring junior engineers
The Ohio State University
Master of Science (M.S.), Computer Science and Engineering
January 1, 2013 – January 1, 2015
Guru Gobind Singh Indraprastha University
Bachelor of Technology (B.Tech.), Computer Science and Engineering
January 1, 2009 – January 1, 2013
Uber
Software Engineer
January 1, 2018 – Present
Greater Seattle Area
IBM
Machine Learning Engineer
September 1, 2015 – January 1, 2018
Denver
The Ohio State University
Graduate Teaching Assistant
August 1, 2014 – December 1, 2014
The Ohio State University
Graduate Research Assistant
January 1, 2014 – May 1, 2015
Indian Institute of Science
Summer Research Assistant
June 1, 2012 – August 1, 2012
University of Hyderabad, Image Processing Lab
Strabus software solutions
Summer Intern
June 1, 2011 – July 1, 2011
Restaurant Management System
August 1, 2014 – December 1, 2014
Created a massively multi-threaded synchronization module for simulating a restaurant. Customers, waiters, chefs were simulated as threads while tables as resources. Objective was to get deeper insights on synchronized multi-threaded systems and resource allocation
Classification and Association Rule Mining in Document Database
August 1, 2014 – December 1, 2014
Given a document database, perform clean-up tasks, construct different feature vectors. Classification, Clustering and Association-rule mining will be incorporated into the project. Coding is being done in Python. Potential use of the Weka/Orange tool.
Automatic Best Image Segmentation Selector
May 1, 2014 – May 1, 2015
Worked on a project which picks the best segmentation corresponding to an image Used stable segmentation approach with normalized cuts and normalized tree partitioning algorithm. Looked at various feature spaces, similarity measures and scale parameters to figure out the number of segments in an image automatically. Used Microsoft's object recognition database. To be incorporated into a semantic context based object recognition framework. Project funded by Air Force Research Labs, Dayton.
Query Builder and Vizualizer
January 1, 2014 – April 1, 2014
Designed a reverse query mapper. Given a subset of a table(s) from a database, the system generates the simplest SQL query which would have produced that output. Coded in C++ and used Microsoft SQL as back-end.
Extrapolation of Occluded Stick Figures using Kinect
January 1, 2014 – May 1, 2014
Worked on extrapolating output of stick figures from kinect. Given joint positions of unoccluded gestures, system learns to predict occuded gestures by predicting the joint positions.
Analysis and Performance Optimization of knn technique
August 1, 2013 – December 1, 2013
Implemented a movie query engine that allows users to find a movie of interest by starting the query from a movie that they have already seen. Example query: Iron Man - Robert Downey Jr. + Christian Bale -------> (result) The Dark Knight Showed improvement in performance of KNN by using pre - clustering, k-d trees and locality sensitivity hashing.
A Study of the effect of Occlusion on Gesture Recognition
August 1, 2013 – December 1, 2013
Addressed the problem of occlusion while recognizing gestures in a database. Used Motion History and Motion Energy images for feature vector construction. Tried various methods to be able to recognize gestures which were occluded. Used distance based classification techniques.
LISP Interpreter
August 1, 2013 – December 1, 2013
Implemented a fully functional LISP interpreter in C++
Fingerprint Alignment and Recognition
August 1, 2012 – May 1, 2013
Addresses the problem alignment of fingerprints while recognition of fingerprint images Project was carried out in two parts - first; relied on finding minutia to re-align the fingerprint images and second; the recognition Recognition was done using 3 classifiers - knn, backpropogation and SVM
Comparison of Classification Techniques on ECG data
August 1, 2012 – April 1, 2013
Studied various classification techniques to predict severity of heart disease. Database of heart test parameters taken from UCI Machine Learning Repository.
Face Recognition based Automatic Attendance System
June 1, 2012 – August 1, 2012
Worked on a project which automated the process of attendance using the face recognition technology A picture of a class serves as input from which faces are recognized. A 92% success rate was achieved when prototype was run in one of the university's classes. Coded in C++ and used Intel's OpenCV modules.
Mail Manager
June 1, 2011 – July 1, 2011
Designed a third party mail application for the company. Worked on .NET framework, coded in C# and used Microsoft SQL as back-end.
Cultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards research and academic-style problem-solving, particularly in machine learning and computer vision. While these skills are transferable, the target role of 'Data Analyst' typically requires a more direct focus on business intelligence, reporting, and data visualization tools, which are less explicitly highlighted in the projects. The diversity of projects indicates a broad interest in technical challenges, but their alignment with typical data analyst responsibilities needs further validation. The experience at Uber (Software Engineer) and IBM (Machine Learning Engineer) suggests adaptability to corporate environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and a proactive approach to learning new techniques. The role as a Graduate Teaching Assistant suggests communication and mentoring skills. However, without psychometric test results or interview data, a comprehensive assessment of soft skills and operational fit is limited.