Data Science with less than a year in Machine Learning & Data Visualization.
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Assessing your cultural and operational fit
Analytical Data Scientist with hands-on experience building and deploying Machine Learning models. Skilled in Python, SQL and Data Visualization. Passionate about extracting insights and automating workflows for better business outcomes.
Pallavi Engineering College
Bachelor of Technology · Computer Science (Specialization in Data Science)
August 1, 2020 – June 30, 2024
Sri Aryabhatta Junior College
Intermediate
June 1, 2018 – May 31, 2020
Jeevadan High School
SSC
June 1, 2017 – May 31, 2018
SaiKet Systems
Data Science Intern
January 1, 2024 – February 1, 2024
Mumbai, Maharashtra, India
Birth Rate Analysis
June 1, 2026 – Present
• Developed Machine Learning Linear Regression model to predict birth rates. • Analyzed 5,000 records and presented trends using Power BI dashboards.
Water Quality Prediction
June 1, 2026 – Present
• Built Machine Learning Decision Tree model to predict water quality from physical and chemical indicators. • Analyzed a dataset of 7,000 samples and visualized results with Power BI.
Data Science with Generative AI
Physics Wallah
June 1, 2024 – May 1, 2025
Data Science with Python
Analytics Vidhya Solutions
March 1, 2023 – June 1, 2023
Cultural Fit Analysis
The candidate's projects and internship demonstrate a focus on practical application of data science, which aligns with a results-oriented culture. The diversity in project topics (birth rate, water quality, churn prediction) suggests adaptability and a willingness to tackle different problem domains. The inclusion of Power Pages and Power Apps in the internship indicates exposure to broader business application development, which could be beneficial for cross-functional collaboration. However, with only one short internship and personal projects, the depth of experience in team collaboration and navigating complex organizational dynamics is not clearly evident.
Soft Skills & Operational Fit
The candidate lists problem-solving, team management, time management, risk analysis, leadership, analytical skills, visualization skills, and adaptive thinking as soft skills. While these are valuable, the provided data does not offer specific examples or assessments to validate their operational fit or proficiency in these areas. The internship description mentions streamlining business processes, which hints at operational awareness, but lacks detail.