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Data Science with less than a year in AI/ML and Strong Data Analysis Skills
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Statistics postgraduate from University of Madras with an interest in Data Analytics and data-driven problem solving. Familiar with Python, SQL, Tableau, and basic data analysis techniques through academic, internship, and hands-on projects.Currently looking for opportunities to learn and grow in data analytics and related fields.
University of Madras
Master of Science · Statistics
August 1, 2024 – June 30, 2026
Mar Gregorios College Of Arts & Science
Bachelor of Science · Mathematics
August 1, 2021 – June 30, 2024
SmarTech Infra Solutions
Statistics and ML Intern
May 1, 2025 – July 31, 2025
India
Business Expense Estimation & Year-over-Year (YoY) Analysis Dashboard
June 24, 2026 – Present
• Collaborated in developing an interactive Tableau dashboard under the Naan Mudhalvan initiative to analyze and visualize business expenses. • Categorized financial data into operational, administrative and logistical segments to identify spending patterns and support budget forecasting. • Created detailed Tableau worksheets to track multiple expense components including personnel costs, contracts, insurance, taxes and logistics expenses. • Contributed to the design and integration of the final master dashboard by combining multiple visualizations into a unified analytical view.
Flood Susceptibility Assessment and Prediction for Chennai District Using Statistical Learning and Spatial Hotspot Modeling
June 24, 2026 – Present
• Analyzed multi-year flood data (2015, 2021,2023) using statistical, spatial and machine learning techniques to identify flood-prone regions and major environmental flood drivers. • Applied descriptive statistics, Wilcoxon Rank-Sum tests and logistic regression to evaluate the influence of terrain, hydrological and land-use variables on flood occurrence. • Developed Random Forest flood prediction models achieving ~80% accuracy and ROC-AUC above 0.86 for flood susceptibility prediction. • Performed spatial hotspot analysis and zone-wise flood risk assessment using GIS-based statistical methods. • Proposed mitigation strategies for different urban zones based on dominant flood-driving variables.
Cultural Fit Analysis
The candidate's academic projects and internship demonstrate an interest in applying data science to real-world problems, aligning with a problem-solving culture. The 'Naan Mudhalvan initiative' project suggests an inclination towards collaborative and initiative-driven environments. The breadth of skills (Python, R, SQL, Tableau, GIS, NLP, LLMs) indicates a willingness to learn and adapt to various tools and methodologies. However, the limited professional experience makes it difficult to fully assess cultural fit beyond these initial indicators.
Soft Skills & Operational Fit
The candidate lists collaboration, communication, active listening, and problem-solving as soft skills. Project descriptions indicate collaboration in team settings (e.g., Tableau dashboard project). The internship involved improving extraction accuracy and reducing manual processing time, suggesting an operational focus on efficiency. However, without direct assessment data, the depth of these soft skills and operational fit cannot be fully validated.