Help & Supportcareers@gravityer.com
Data Science with less than a year in ETL, ML, and interactive dashboards.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven Data Analyst and aspiring Data Scientist with an M.Sc. in Statistics and a PG Diploma in Big Data Analytics. Experienced in building end-to-end ETL pipelines, data warehouses, machine learning models, and interactive dashboards. Proficient in Python, SQL and Power BI. Adept at transforming large-scale datasets into actionable insights to support data-driven business decisions. Strong foundation in statistical modelling, data quality management and predictive analytics.
CDAC
PG Diploma in Big Data Analytics (PG-DBDA) · Big Data Analytics
August 1, 2025 – June 30, 2026
Sadguru Gadage Maharaj College
Master of Science (M.Sc.) · Statistics
August 1, 2023 – June 30, 2025
Ajara Mahavidyalaya
Bachelor of Science (B.Sc.) · Statistics
August 1, 2020 – June 30, 2023
AIS Solutions Pvt. Ltd.
Data Analyst Intern
January 1, 2025 – April 1, 2025
Pune, Maharashtra, India
Data Warehouse & Analytics Platform (SQL Server)
June 1, 2026 – Present
Architected a data warehouse using Medallion Architecture (Bronze, Silver, Gold layers) by integrating ERP and CRM datasets for a unified analytics layer. Designed and built automated ETL pipelines using SQL for data extraction, transformation, deduplication, and loading improving data reliability and processing speed. Developed a Star Schema (fact & dimension tables) optimized for analytical queries and BI reporting. Applied window functions for data deduplication and query optimization, significantly improving data accessibility and query performance.
Sales Performance Dashboard (Power BI)
June 1, 2026 – Present
Developed an interactive Power BI dashboard to analyse sales performance across product categories, regions, and time trends, enabling real-time business intelligence. Performed end-to-end ETL using Power Query: data cleaning, transformation, and pivot/unpivot operations for structured reporting. Created advanced DAX measures including Total Sales, Average Order Value (AOV), Customer Count, and Order Count for KPI tracking. Designed intuitive visualizations — KPI cards, bar charts, line charts, pie charts, and dynamic slicers — to deliver actionable insights on seasonal trends and regional performance.
Partial Face Detection using Deep Learning & Machine Learning.
June 1, 2026 – Present
Designed and deployed an end-to-end deep learning pipeline for partial and non-frontal face recognition using MTCNN for face detection and FaceNet (CNN-based model) for generating high-dimensional facial embeddings. Applied cosine similarity with confidence thresholding to accurately classify known vs. unknown faces under occlusion and low-visibility conditions. Engineered robust preprocessing and feature extraction techniques to improve model performance in challenging real-world environments. Built a real-time face recognition application using Streamlit with live camera integration for user-facing deployment. Evaluated model performance using train-test split, accuracy, precision, recall, F1-score, and classification reports.
Predictive Analysis & Visualisation of Indian Automobile Market
June 1, 2026 – Present
Built a predictive analytics pipeline on a 5,975-record Indian automobile dataset to forecast used-car prices using machine learning. Performed EDA and statistical analysis to identify key price-driving factors such as vehicle power and manufacturing year. Applied feature selection techniques to improve model efficiency and reduce complexity. Compared Linear Regression, Random Forest, and XGBoost models; selected XGBoost as the best-performing model with R2 = 0.856 and RMSE = 4.58. Conducted hypothesis testing and derived market insights related to fuel type, transmission, and post-COVID market trends.
R Software - Academic Certification
Unknown
June 1, 2026 – Present
Python for Data Science – NPTEL
IIT Madras
June 1, 2026 – Present
Data Associates
Symbiosis Statistical Institute
June 1, 2026 – Present
Participant - National Conference on Modern Applications of Statistical Science (NCMASS-24)
Unknown
June 1, 2026 – Present
Research Methodology – NPTEL
IIT Madras
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse range of applications, from data warehousing and business intelligence to deep learning for face detection and predictive analytics for market analysis. This breadth of interest and application, combined with an internship experience, suggests adaptability and a willingness to tackle varied challenges, which is a positive indicator for cultural fit in a dynamic data science environment. The certifications also show a commitment to continuous learning.
Soft Skills & Operational Fit
The candidate lists analytical thinking, problem-solving, attention to detail, communication, time management, and team collaboration as soft skills. These are crucial for a Data Science role, indicating a good operational fit. The project descriptions also reflect these skills in practice, particularly in data cleaning, EDA, and dashboard development.