Help & Supportcareers@gravityer.com
Hi, I am Pranay Chandekar, Machine Learning Engineer by profession. If you find my projects interesting and wish to engage in a candid chat then get in touch.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
phenompeople
Data Scientist
June 20, 2026 – Present
langchain-fastapi-app
August 10, 2023 – August 10, 2023
This is a sample langchain app created in FastAPI framework
View Projectmlflow-server
January 22, 2023 – January 24, 2023
Host MLFlow Tracking Server and Model Registry as a containerized application on Kubernetes
View Projectaws-lambda-docker
April 30, 2022 – January 23, 2023
This repository is a plug and play template to create containerized AWS Lambda Functions
View Projectnumba_cosine
December 22, 2019 – December 22, 2019
This repository contains the experiment with numba.
View Projectml-prediction-web-service
October 16, 2019 – February 5, 2024
A simple python web service to host an ML model for prediction.
View Projectdsa
October 13, 2019 – October 15, 2019
This project contains the Python Implementation of DSA concepts covered in mycodeschool videos.
View Projectfasttext-embeddings-with-flair
July 11, 2019 – May 2, 2025
This project contains the code to use custom fasttext embeddings with flair framework.
View Projectkeras-sagemaker-train
June 7, 2019 – March 24, 2023
A project cum tutorial which will help you understand and setup your custom keras project in Amazon SageMaker.
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and technical, indicating a strong individual drive for learning and experimentation. The current role as 'Data Scientist' aligns with the target role. However, the lack of team-based or collaborative project descriptions makes it difficult to assess cultural fit beyond individual technical contribution. The diversity of projects, while technically focused, shows a breadth of interest in ML deployment, core ML, and web services.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, indicating a focus on technical output. No psychometric or English test results are available for evaluation.