SATYAJIT SWAIN

AI Engineer

https://www.opentalent.in/satyajit-swain

Bhubaneswar, indiaMember since July 26, 2025

Key Strengths

Candidate is pursuing an M.Sc. in Data Science, indicating foundational academic interest in the target role.
Demonstrates familiarity with core AI/ML concepts, including data analysis, machine learning, and natural language processing.
Has practical project experience in recommendation systems (collaborative filtering) and text classification (TF-IDF, SimCSE, Logistic Regression, SVM, Naive Bayes), which are directly relevant to an AI Engineer role.
Proficient in Python, a key language for AI/ML development, and has exposure to data visualization tools like Tableau and Jupyter.
Has some exposure to DevOps basics, containerization (Docker), and CI/CD pipelines through an internship, which can be beneficial for MLOps.

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 32% is a substantial concern for cultural fit. This score suggests potential difficulties in areas such as team collaboration, adaptability, and managing workplace stress, which are fundamental for a positive and productive team environment. Further assessment would be required to understand the root causes of these low scores and their potential impact on team dynamics.

Soft Skills & Operational Fit

The psychometric test score of 32% (161/500) indicates significant concerns regarding logical reasoning, work attitude, stress handling, and team collaboration. These areas are critical for operational effectiveness and integration into a professional environment. While the resume lists 'Problem Solving', 'Teamwork', and 'Analytical Thinking' as core skills, the test results contradict these self-assessments, suggesting a potential mismatch in expected workplace behaviors and cognitive abilities.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Key Strengths

Candidate is pursuing an M.Sc. in Data Science, indicating foundational academic interest in the target role.
Demonstrates familiarity with core AI/ML concepts, including data analysis, machine learning, and natural language processing.
Has practical project experience in recommendation systems (collaborative filtering) and text classification (TF-IDF, SimCSE, Logistic Regression, SVM, Naive Bayes), which are directly relevant to an AI Engineer role.
Proficient in Python, a key language for AI/ML development, and has exposure to data visualization tools like Tableau and Jupyter.
Has some exposure to DevOps basics, containerization (Docker), and CI/CD pipelines through an internship, which can be beneficial for MLOps.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit