Rajat Goyal
Data ScientistSDE at Microsoft, CSE NITW'23
Microsoft
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
SDE at Microsoft, CSE NITW'23
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Microsoft
Data Scientist
June 21, 2026 – Present
Se-WaveNet
October 31, 2024 – October 31, 2024
This project focuses on a squeeze and excitation (SE) mechanism applied to the Wav2Vec2.0 model for automatic speech recognition. Performance evaluation using MFCC feature distance and word error rate (WER) indicated improved feature representation.
View ProjectAdvanced-Pharmacy-Management-System-Database-Design
June 9, 2022 – June 9, 2022
It Consists Medicine Delivery and doctor consultancy Database Design Along with Simple Pharmacy Database Management. Worked on the conversion of entity relationship diagram into relational models and Complete Implementation The database was normalized to reduce data redundancy,
View ProjectA-star-Visulization
June 9, 2022 – June 9, 2022
A* Algorithm is Implemented and can be visualized using python.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a mix of personal projects, some directly related to data science ('Se-WaveNet', 'ML', 'A-star-Visulization') and others more general programming or academic ('Portfolio', 'test_java', 'CNS', 'Advanced-Pharmacy-Management-System-Database-Design'). The current role as a Data Scientist at Microsoft aligns well with the target role. However, the diversity of projects outside core data science, without clear explanations of their relevance, makes a precise cultural fit assessment challenging. The experience level is listed as 0, which contradicts the current role at Microsoft, suggesting a potential data inconsistency or a very recent start.
Soft Skills & Operational Fit
The candidate's profile indicates an interest in machine learning and data science through personal projects. However, without psychometric test results or interview data, it is difficult to assess soft skills like logical reasoning, work attitude, stress handling, or team collaboration.