Help & Supportcareers@gravityer.com
Data Science with 1+ years in Data Analysis & Solution Design
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Motivated Computer Science graduate with 2.5 years of experience bridging business and technology through data analysis, requirements documentation, and solution design. Skilled in understanding and translating business needs into structured analytical solutions using SQL, Python, Power BI, and Tableau. Experienced in working cross-functionally with stakeholders, documenting requirements, performing systems and data analysis, and delivering digital solutions that balance business value with technical feasibility. Eager to grow in a Business Analysis and Solution Design environment at Capgemini.
Rajiv Gandhi College of Engineering
B.E. · Computer Science & Engineering
August 1, 2021 – June 30, 2025
S-Logix (OPC) Pvt. Ltd.
Business Analyst / Data Analyst
March 1, 2023 – November 1, 2024
Chennai, Tamil Nadu, India
HR Analytics Solution Design & Dashboard
June 23, 2026 – Present
Led a 3-member Agile team to gather requirements from HR stakeholders, analyze 10,000+ employee records, and design a digital analytics solution for workforce trend and attrition monitoring. Documented business requirements, data models, and solution design decisions to align development with HR objectives; identified quick-win metrics and long-term KPI tracking capabilities. Developed 8+ Power BI dashboards with drill-through reports, KPI scorecards, and forecasting models, reducing reporting time by 40% and improving stakeholder visibility. Performed statistical analysis and regression modeling to identify top attrition risk factors; presented findings to HR leadership to support strategic retention planning.
Sales Performance Solution & ETL Pipeline
June 23, 2026 – Present
Analyzed business requirements across 5 units to design an end-to-end ETL pipeline and reporting solution balancing immediate analytical needs with scalable data architecture. Identified 3 underperforming regions responsible for 18% revenue loss by bridging business questions with data analysis; recommended targeted actions to business stakeholders. Developed interactive Power BI dashboards with DAX measures, forecasting models, and KPI tracking; standardized reporting to improve cross-functional data-driven decision-making. Documented solution design, data flows, and integration architecture to ensure alignment between business goals and technical delivery.
Customer Churn Prediction & Business Insights
June 23, 2026 – Present
Partnered with stakeholders to define business problem, analyze churn drivers, and design a predictive analytics solution that translated data outputs into actionable business recommendations. Performed end-to-end data analysis including EDA, feature engineering, and classification modeling (Logistic Regression, Random Forest), achieving 87% prediction accuracy. Created Tableau dashboards and business reports communicating churn risk segments and retention strategies to non-technical stakeholders. Documented the solution design, model assumptions, and business rules to facilitate review, quality assurance, and future enhancements.
Python for Data Science
Infosys Springboard
June 1, 2026 – Present
Data Engineering & Big Data
HCL GUVI
June 1, 2026 – Present
Career Essentials in Data Analysis
Microsoft & LinkedIn Learning
October 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, covering HR analytics, customer churn prediction, and sales performance, indicates adaptability and a broad interest in applying data science across different business domains. Their experience in leading a team and collaborating with various stakeholders suggests a team-oriented and communicative approach, aligning well with collaborative work cultures. The focus on delivering business value through data solutions also points to a results-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong stakeholder management, cross-functional collaboration, and data storytelling skills, which are crucial for a Data Science role. Their experience in Agile and Scrum methodologies indicates a good operational fit for dynamic project environments. The ability to balance quick wins with scalable architecture suggests a practical and strategic mindset.