Ritika

Data Scientist

https://talent.gravityer.com/ritika-6

SDE

Adobe

Key Strengths

Demonstrated interest in Data Science and Machine Learning through various personal projects.
Experience with Python and Jupyter Notebook for data-related tasks.
Exposure to deep learning frameworks (VGG16, RNNs) for image processing and NLP.
Practical application of clustering algorithms (Louvain clustering) in recommendation systems.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong inclination towards data science and machine learning, which aligns with the target role of Data Scientist. However, the projects are all personal and lack diversity in terms of team collaboration or real-world business impact. The experience section lists a current role as 'Data Scientist' at Adobe starting in 2026, which is in the future, indicating a potential data entry error or a planned future role. This makes it difficult to assess current professional experience and cultural fit within a corporate environment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.

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Projects

Optiised-Ensemble-Model-For-Heart-Disease-Detection

January 2, 2023 – January 2, 2023

Optiised-Ensemble-Model-For-Heart-Disease-Detection — GitHub repository

View Project

Product-Recommendation-Engine

April 7, 2021 – April 27, 2021

Flask app for a collaborative product recommendation engine that uses Louvain clustering.

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WildSprint-Blockchain

March 22, 2021 – March 22, 2021

Ethereum Blockchain component of WildSprint, a web application that incentivises donations to wildlife preservation organisations and makes them easily accessible, secure and transparent.

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Brain-Tumour-Detection

March 15, 2021 – April 14, 2021

Image processing DA

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IP-Operations

February 24, 2021 – March 24, 2021

Code for basic image processing operations

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Abstractive-text-summarisation-of-GitHub-issues

February 1, 2021 – April 27, 2021

Uses RNNs to create a sequence to sequence model for abstractive text summarisation.

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leaf-disease-detection

November 16, 2020 – January 19, 2021

Using VGG16 with other image processing techniques to detect diseases on the leaf of a plant

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kernel-convolution

November 12, 2020 – February 8, 2021

Parallelisation of image kernel convolution

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Dialogflow-chatbot

November 7, 2020 – February 8, 2021

AI Assignment: A PsychiatricBot that can answer mental health queries, schedule appointments and determine MBTI personality

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8086.js

August 28, 2020 – September 26, 2021

A basic web-based 8086 emulator built with Javascript :rocket:

View Project

Key Strengths

Demonstrated interest in Data Science and Machine Learning through various personal projects.
Experience with Python and Jupyter Notebook for data-related tasks.
Exposure to deep learning frameworks (VGG16, RNNs) for image processing and NLP.
Practical application of clustering algorithms (Louvain clustering) in recommendation systems.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.

Ritika

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit