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Data Science with less than a year in data analysis and machine learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Computer Science graduate (CSE - AIML) with hands-on experience in data analysis, machine learning, and Python development. Strong foundation in exploratory data analysis (EDA), model building, and data visualization. Seeking an entry-level Data Analyst, Junior Data Scientist, or Machine Learning Intern role.
Kits-Akshar Institute of Technology,JNTUK
B.Tech · CSE(AIML)
August 1, 2021 – June 30, 2025
Viveka Junior College for Girls
Intermediate · MPC
June 1, 2019 – May 31, 2021
Viveka Medical & IIT Academy
Secondary
June 1, 2018 – May 31, 2019
AI for Drug Discovery
June 16, 2026 – Present
Designed an AI-based application to assist early-stage drug discovery. Performed data preprocessing and exploratory data analysis using Pandas and NumPy. Built and evaluated machine learning models to predict potential drug candidates. Integrated Generative AI concepts and developed a user interface using Gradio. Achieved 96% prediction accuracy, improving efficiency in candidate identification.
Python Full Stack Development
Codegnan
June 1, 2026 – Present
AI, Machine Learning & Data Science
IIDT Blackbucks
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic project demonstrates initiative and a focus on practical application of AI/ML. The certifications in Python Full Stack Development and AI/ML/Data Science show a proactive approach to learning and skill development. The target role of Data Science aligns well with the academic background and project experience. However, the lack of diverse project types or team-based experiences limits a deeper assessment of cultural fit.
Soft Skills & Operational Fit
The candidate's project description indicates an ability to work on complex problems and deliver measurable results (96% prediction accuracy). The academic background in AIML suggests a foundational understanding of problem-solving and analytical thinking. However, without specific behavioral or teamwork data, it's difficult to assess operational fit beyond technical aptitude.