Data Science with 4+ years in Data Analysis & Machine Learning
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Statistics postgraduate with professional experience in compliance reporting and operational analytics. Skilled in data analysis, machine learning, and dashboard development through end-to-end projects. Proficient in Python, SQL, Excel, and Power BI, with a solid foundation in applying data-driven solutions to real-world problems.
University of Kerala
B.Sc. Mathematics · Mathematics
N/A – June 30, 2018
University of Kerala
M.Sc. Statistics · Statistics
N/A – June 30, 2020
Allianz Services India Pvt. Ltd.
Helpdesk Executive - Facilities
July 1, 2023 – Present
Thiruvananthapuram, Kerala, India
Capstocks & Securities India Pvt. Ltd.
Junior Executive - Compliance
February 1, 2021 – July 1, 2023
Thiruvananthapuram, Kerala, India
Student Social Media Addiction Prediction – ML Web Application
June 23, 2026 – Present
Developed and deployed machine learning models to assess student social media addiction levels and their impact on academic performance.
View ProjectRetail Sales Analytics & Forecasting Dashboard – Power BI
June 23, 2026 – Present
Developed an interactive Power BI dashboard using a star schema data model, incorporating DAX-based KPIs, customer and product insights, logistics analysis, and time-series sales forecasting for data-driven decision-making.
View ProjectFootball Match Performance Analysis – Web Scraping & EDA
June 23, 2026 – Present
Developed an end-to-end data analysis pipeline by scraping real-world football data, followed by data cleaning, exploratory analysis, and visualization to uncover key performance trends and insights.
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates initiative and a proactive approach to learning and applying data science skills. The projects cover diverse areas like social media addiction, retail sales, and sports analytics, indicating a broad interest in applying data science to various domains. While professional experience is not directly in data science, the candidate's educational background and personal projects show a strong drive towards the target role. The current and previous roles, however, are not aligned with a typical data science career path, which might require a stronger justification of their transition and motivation.
Soft Skills & Operational Fit
The candidate's professional experience, though not directly in data science, indicates strong operational skills such as data tracking, analysis of operational patterns, monitoring SLAs, and report generation. These roles suggest attention to detail, reliability, and the ability to work with data to support decision-making, which are transferable to a data science role. The candidate's project descriptions are clear and concise, indicating good communication skills.