Senior Engineer at BOSCH https://medium.com/@nikitamalviya
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Bosch
Data Scientist
June 21, 2026 – Present
microsoft-azure-python-helper
August 22, 2024 – June 9, 2025
microsoft-azure-python-helper — GitHub repository
View Projectobject-detection-helper
August 21, 2024 – August 22, 2024
This repository contains the common source codes for object detection tasks.
View Projectfile-converter-python
May 18, 2024 – May 19, 2025
contains code to convert file from one format to another, like pdf to jpg, jpgs to pdf, tif to pdf, tif to jpg,..,etc
View Projectcomputer-vision-utilities
May 2, 2024 – June 17, 2025
having common codes used in computer vision tasks
View Projectkitti-dataset-format-visualization
February 27, 2024 – February 27, 2024
This repo contains the code which can be used to visualize the 2D and 3D bounding box present in kitti dataset using label_2 and calib folder.
View Projectmodel-training-utils
February 27, 2024 – February 27, 2024
contains code files related to neural network model training
View Projectchurn-in-telecoms-dataset
July 10, 2020 – July 10, 2020
Customer Churn Analysis on Churn in Telecom's dataset ; classification , feature engineering, ensembling.
View Projectimage-classification
October 2, 2019 – March 5, 2020
It is built using Keras framework which can classify ‘N’ number of classes on feeding unlabeled images and can predict their class belongings. The entire project setup can be done in the configuration file. It can accept csv, json and unsplit dataset as input, integrated to preprocessing template which can be easily modified to process the particular input dataset. It has training, testing, and prediction phases interfused with foolproof validations. User can select a predefined model or can add a new model body and can pass all the tuning parameters from the configuration file. The trained models, weights and tblogs will be saved, maintaining the checkpoints.
View Projectreal-time-facial-expression-recognition
March 5, 2019 – November 22, 2022
This project detects the emotions in real time. It covers 5 emotions which are Surprise, Happy, Anger, Sad and Disgust.The mini Xception model is trained, hence achieved 80% accuracy. Fer2013 dataset is used to train the model.
View Projectgradient-descent
November 9, 2018 – April 30, 2020
This is an implementation problem of Gradient Descent in which you can see the descendants of the point on the plane to reach the minima with the help of the graph to understand the working of gradient descent. Demo code using python and matlab are available.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and demonstrate a strong interest in data science and machine learning. However, the lack of team-based projects or contributions to open-source initiatives makes it difficult to assess cultural fit comprehensively. The current role at Bosch as a Data Scientist aligns with the target role, but the start date being in the future (2026) suggests this might be a prospective or incorrectly entered detail, making it hard to gauge current professional experience.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions indicate a focus on technical implementation.