Data Science with less than a year in data analysis, machine learning, and programming.
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Vikram Singh is an aspiring Data Science professional currently pursuing a B.Tech in Information Technology. With 0.5 years of internship experience as a Credit Analyst Intern and Data Engineer Intern, he has developed strong skills in Python, SQL, data cleaning, EDA, and machine learning model development. His project work includes building a Crop Analysis System and a Customer Lifetime Value Prediction model, demonstrating his ability to apply data-driven approaches to real-world problems. He is proficient in data visualization tools and eager to leverage his technical expertise for business insights.
Swami Keshvanand Institute of Technology, M & G
B.Tech · Information Technology (IT)
August 1, 2022 – June 30, 2026
Veena Dharini Bal Vidhya Sr Sec School
Class 12
June 1, 2018 – May 31, 2020
Veena Dharini Bal Vidhya Sr Sec School
Class 10
N/A – Present
Advarisk SLO Technologies
Credit Analyst Intern
January 1, 2026 – June 1, 2026
India
Proxenix
Data Engineer Intern
July 1, 2024 – August 1, 2024
Jaipur, Rajasthan, India
Customer Lifetime Value Prediction (Machine Learning)
June 24, 2026 – Present
• Applied K-Means Clustering and RFM Segmentation for customer analysis. • Performed data cleaning, feature engineering, and EDA. • Built a model achieving 88% accuracy. • Created 8+ Plotly dashboards for insights.
Crop Analysis System
June 24, 2026 – Present
• Designed and developed an interactive agricultural data analysis dashboard using R Shiny. • Integrated Google Authentication, reducing unauthorized access attempts by 90%. • Enhanced data visualization using ggplot2 and 3D charts. • Processed crop and rainfall datasets to identify yield trends.
Secured Rank 5 in Codeformers Coding Competition
Unknown
January 1, 2023 – Present
Elite certification in Developing Soft Skills and Personality
NPTEL – IIT Kanpur
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative and a practical application of data science concepts. The 'Crop Analysis System' project shows an interest in diverse applications of data analysis, while the 'Customer Lifetime Value Prediction' project aligns well with business-oriented data science roles. The internships, though short, provide exposure to real-world data challenges in credit analysis and data engineering. The breadth of skills listed (Python, SQL, R Shiny, ML algorithms) suggests adaptability and a willingness to learn new technologies, which are positive indicators for cultural fit in a dynamic data science environment.
Soft Skills & Operational Fit
The candidate has an 'Elite certification in Developing Soft Skills and Personality,' suggesting a foundational understanding of professional conduct and teamwork. Project descriptions indicate an ability to work on structured tasks and contribute to data-driven decision-making. However, without specific psychometric test results, a deeper assessment of work attitude, stress handling, and team collaboration is not possible.