Ipsita Surbhi

Chhattisgarh Swami Vivekanand Technical University

Bhilai, Chhattisgarh, India

Since April 19, 2026

About

I am a Computer Science student with hands-on experience in MERN stack development, having built projects like QuickCab using React.js, Node.js, Express.js, and MongoDB with RESTful APIs. I have also developed an AI-based tool, PostCraft, and gained experience handling real-time data during my internship at IIT Patna. I focus on writing clean, scalable code and building efficient web applications.

Skills

JavaJavaScriptRest ApiMongoDBDevOpsFront-endSQLStatisticsGit-GitHubMachine LearningPower BIPythonHTML5Problem SolvingAPI IntegrationMERN StackPyTorchProgrammingNode.jsReact.jsWeb DevelopersSoftware DevelopersData PreprocessingPostmanDocker / KubernetesTensorFlowWeb DesignersMysqlCSSFull-stackTableauAI EngineerLLM applicationsAI/ML FrameworksPandas, NumPyData sciencePython/R

Education

Chhattisgarh Swami Vivekanand Technical University

Bachelor of Technology · Computer Science Engineering

November 13, 2022 – May 27, 2026

Key Strengths

Strong academic background in Computer Science Engineering with a 7.85 CGPA.
Demonstrated proficiency in MERN stack (React.js, Node.js, Express.js, MongoDB) through the QuickCab project, showcasing full-stack development and API design capabilities.
Broad technical skill set including Python, Java, ML/AI frameworks (TensorFlow, PyTorch), and DevOps tools (Docker, Kubernetes), indicating a strong learning aptitude.
Proactive in gaining practical experience through a research internship and multiple hands-on projects.
Significant mismatch for a 'Lead MERN Engineer' role due to zero professional experience and current student status. The candidate demonstrates strong potential as a junior or entry-level MERN developer but lacks the leadership, architectural, and extensive professional experience required for a lead position.

Skill Analysis

Insufficient Data

★★★★★

No completed technical tests were provided for evaluation.

Strengths

No technical assessment data available.

Limitations

No technical assessment data available to evaluate specific coding or system design skills.

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 67.8% suggests an average fit regarding work attitude, stress handling, and team collaboration. There are no significant red flags, but also no outstanding indicators of exceptional cultural alignment based solely on this score. Further interaction would be needed to fully assess cultural fit.

Soft Skills & Operational Fit

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