Interested in building solutions for real world ML applications. Experience with varied forms of practical data, including speech, text, images & high-dim data.
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Fidelity Investments
Data Scientist
June 16, 2026 – Present
NL2SQL
June 10, 2024 – June 28, 2025
Tutorials for converting natural language to SQL (NL2SQL) to fetch required data.
View Projectfinbert_embedding
December 23, 2019 – May 24, 2023
Token and sentence level embeddings from FinBERT model (Finance Domain)
View ProjectFaceEmotion_ID
November 22, 2018 – January 7, 2019
Detects Face using Haarcascades and further detects emotion in bounded face (trained a CNN emotion detector model)
View ProjectFace_ID
October 25, 2018 – November 22, 2018
Face Recognition using MTCNN face detector and FaceNet (pre-trained by davidsandberg) based identification.
View ProjectChange-Detection-in-Satellite-Imagery
November 23, 2017 – June 6, 2025
It employes Principal Component Analysis (PCA) and K-means clustering techniques over difference image to detect changes in multi temporal images satellite imagery.
View ProjectSpeaker-identification-using-GMMs
November 14, 2017 – October 4, 2019
It uses GMM to train a speaker identification model. The training and testing has been done on subset (34 speakers) from VoxForge data corpus.
View ProjectTopic-Modelling-on-Wiki-corpus
August 28, 2017 – December 5, 2018
It uses Latent Dirichlet Allocation algorithm to discover hidden topics from the articles. It is trained on 60,000 articles taken from simple wikipedia english corpus. Finally, It can extract the topic of the given input text article.
View ProjectPyGender-Voice
June 13, 2017 – June 14, 2017
It uses GMM to train a gender detector model. The testing has been done on subset of Google's AudioSet corpus.
View ProjectImage-compression-with-Kmeans-clustering
March 7, 2017 – October 25, 2018
A lossy compression to illustrate an application of K-means clustering algorithm
View ProjectMail-Spam-Filtering
February 3, 2017 – February 3, 2017
It uses machine learning models (Multinomial NB & SVM) to predict whether the email is spam or ligitimate on two corpus namely Ling-spam corpus and Euron-spam corpus.
View ProjectCultural Fit Analysis
The candidate's projects are diverse within the data science domain, indicating a broad interest in various applications of machine learning and AI. The projects are all personal, which suggests self-motivation and initiative. However, without information on team projects or contributions, assessing collaboration and broader cultural fit is challenging. The current role as 'Data Scientist' at Fidelity Investments aligns well with the target role, but the start date being in the future (2026) suggests this is a prospective or future role, or an error in the data, making current professional experience difficult to assess.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions are concise and technical, but do not offer insights into collaboration, problem-solving approach, or communication style.