Help & Supportcareers@gravityer.com
Data Analyst with 1+ years in Business Intelligence & AWS
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Business Intelligence and Data Analyst with hands-on experience in SQL, Python, Power BI, Tableau, Excel, ETL, data visualization, exploratory data analysis, root cause analysis, statistical analysis, and AWS-based data workflows. Experienced in building dashboards, extracting and transforming datasets, analyzing business trends, preparing reporting-ready data models, and delivering actionable insights for data-driven decision-making. Seeking a Business Intelligence Engineer role to contribute to scalable BI solutions, automated reporting, DSP analytics, data pipelines, stakeholder reporting, and business performance optimization.
Lovely Professional University
Bachelor of Technology
August 1, 2020 – July 1, 2024
Synolase India Pvt. Ltd.
Data Analyst
July 1, 2024 – Present
Bengaluru, Karnataka, India
DSP Advertising Campaign Performance Analytics Platform
June 20, 2026 – Present
• Built an end-to-end advertising analytics platform to analyze campaign performance across impressions, clicks, conversions, spend, revenue, CTR, CPC, CPA, and ROAS. • Processed 1M+ synthetic ad event records using Python and SQL to clean raw logs, remove duplicates, handle missing values, and create campaign-level summary tables. • Created SQL queries using joins, CTEs, window functions, aggregations, and date-based analysis to track daily and weekly campaign performance. • Designed Power BI dashboards for campaign managers to monitor top-performing campaigns, low-ROI segments, conversion trends, and budget utilization. • Used AWS S3 and Athena concepts to simulate cloud-based querying of large advertising datasets for BI reporting. • Identified underperforming campaigns and suggested budget reallocation opportunities that improved simulated ROAS by 18%.
Automated ETL and Data Quality Monitoring Pipeline
June 20, 2026 – Present
• Developed an automated ETL workflow to extract raw CSV data, transform business fields, validate records, and load cleaned datasets for reporting. • Implemented 15+ data quality checks including null validation, duplicate detection, schema checks, outlier detection, date validation, and referential consistency. • Created Python scripts using Pandas and NumPy to automate data cleaning, feature preparation, and summary report generation. • Used SQL to build cleaned fact and dimension-style reporting tables for business intelligence and dashboarding use cases. • Prepared Power BI dashboards to show data quality score, rejected records, missing value trends, and pipeline processing status. • Reduced manual validation effort by 40% through automated checks and reusable data preparation logic.
E-Commerce Sales and Operations BI Dashboard
June 20, 2026 – Present
• Built a business intelligence dashboard to track revenue, orders, product performance, customer segments, cancellation rate, and delivery status. • Created SQL queries to analyze sales trends, monthly revenue, top-selling products, repeat customers, region-wise performance, and delayed orders. • Designed Power BI data model with fact and dimension tables for customers, products, orders, payments, and delivery status. • Developed DAX measures for total revenue, average order value, conversion rate, repeat customer rate, and month-over-month growth. • Added slicers, drill-downs, KPI cards, and trend visuals to support quick business decision-making. • Improved reporting efficiency by 35% by replacing manual Excel tracking with an interactive Power BI dashboard.
Credit Risk Analysis and Default Risk Dashboard
June 20, 2026 – Present
• Processed loan application data using SQL and Python with features such as income, credit score, loan amount, and repayment history. • Performed data cleaning, feature engineering, cross-validation, and model tuning using Logistic Regression and XGBoost. • Achieved 95% recall in identifying high-risk borrowers and created Power BI dashboards for default risk reporting. • Enabled simulation of improved loan approval policies that reduced default risk exposure by 22%.
Data Visualization with Tableau Specialization
University of California, Davis
June 1, 2026 – Present
IBM Cloud Essentials
edX
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from credit risk analysis to advertising campaign performance and e-commerce BI, indicates adaptability and a broad interest in applying data analysis across different domains. The explicit mention of collaboration and stakeholder communication in the professional summary and job description suggests a team-oriented mindset. The pursuit of certifications further highlights a commitment to continuous learning and professional development, which are positive cultural indicators.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills, analytical thinking, and a collaborative approach through project descriptions. The ability to translate complex data into actionable insights for stakeholders indicates good operational fit for a data-driven role. The focus on reducing manual effort and improving efficiency aligns with operational excellence.