Help & Supportcareers@gravityer.com
Data Science with less than a year in SQL, Power BI, Python, 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
Highly motivated Computer Science Engineering student specializing in AI/ML, with a strong foundation in data analytics, machine learning, and business intelligence tools. Experienced in building interactive dashboards, analyzing complex datasets for churn prediction and fraud detection, and evaluating product performance through A/B testing. Eager to apply analytical and technical skills to real-world challenges in a data-driven environment.
Shri Ramdeobaba College of Engineering and Management, Nagpur
B.Tech · Computer Science and Engineering (AI/ML Specialization)
August 1, 2022 – June 30, 2026
E-Commerce Sales Analytics Dashboard
January 1, 2022 – January 1, 2026
Built an interactive Power BI dashboard tracking revenue, orders, profit margin, customer segments, product categories, and regional performance. Wrote SQL queries using joins, CTEs, aggregations, date functions, and window functions to prepare clean analysis-ready datasets. Created KPI cards, trend charts, slicers, and repeat-purchase analysis to support sales performance review and business reporting.
Customer Churn Analysis and Retention Insights
January 1, 2022 – January 1, 2026
Analyzed customer behavior data to identify churn patterns across tenure, contract type, payment method, service usage, and support interactions. Performed data cleaning, missing value treatment, feature engineering, EDA, and correlation analysis using Pandas and NumPy. Built Tableau dashboards showing churn rate by customer segment and highlighted high-risk groups for targeted retention campaigns.
Banking Transaction Fraud Analytics
January 1, 2022 – January 1, 2026
Explored transaction-level banking data to detect suspicious patterns by amount, location, time, merchant type, and account behavior. Used SQL and Python for data extraction, outlier detection, class imbalance handling, and fraud-pattern visualization. Created risk indicators including unusual transaction frequency, high-value transaction spikes, and location mismatch signals.
Product Funnel and A/B Testing Analysis
January 1, 2022 – January 1, 2026
Analyzed user journey data across acquisition, signup, activation, purchase, and retention stages to identify major funnel drop-offs. Calculated conversion rate, retention rate, cohort trends, and segment-wise performance using SQL aggregations and Python analysis. Evaluated A/B test results using statistical significance checks and recommended the better-performing product variant.
AWS Certified Cloud Practitioner
AWS
June 1, 2026 – Present
Architecting Solutions on AWS
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive learning attitude and an interest in diverse data science applications (e-commerce, banking, customer behavior). The AI/ML specialization aligns well with a Data Science target role. The breadth of tools and techniques used suggests adaptability and a willingness to explore different solutions. However, the lack of professional experience limits the assessment of collaboration and workplace cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate business problems into analytical tasks and present findings clearly. The academic nature of projects suggests a structured approach to problem-solving. However, without direct work experience, it's difficult to assess operational fit, teamwork, or stress handling under real-world pressures.