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Microsoft
Data Scientist
June 16, 2026 – Present
Multilabel-Toxic-Comment-Detection-and-Classification
May 12, 2021 – May 23, 2023
Toxic comments refers to hatred online comments classified as disrespectful or abusive towards individual or community. With a boom of internet, lot of users are brought to online social discussion platforms. These platforms are created to exchange ideas, learning new things and have meaningful conversations. But due to toxic comments many users are not able to put their points in online discussions. This degrades quality of discussion. And if the comment is toxic then classify the comments into different categories to examine the type of toxicity. We will utilize different machine learning and deep learning algorithms on our dataset and select the best algorithms based on our evaluation methodology. Moving forward we seek to attain high performance through our machine learning and deep learning models which will help in limiting the toxicity present on various discussion sites.
View ProjectAutoSuggest
April 7, 2019 – October 9, 2020
It uses trie data structure for auto suggesting various possible words of given prefix string
View ProjectPython-Media-Player
October 13, 2018 – October 9, 2020
It is basic Python Media Player created using python3, Tkinter GUI and vlc bindings
View ProjectCultural Fit Analysis
The candidate's projects show a mix of interests (media player, data structures, machine learning). The 'Multilabel-Toxic-Comment-Detection-and-Classification' project aligns with data science, but the other projects ('Python-Media-Player', 'AutoSuggest') are less directly relevant to a senior Data Scientist role, suggesting a broader interest set rather than deep specialization. The experience level is listed as 0, which contradicts the current role at Microsoft, making it difficult to accurately assess cultural fit for a senior role without further clarification.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.