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Data with less than a year in Python, SQL & Power BI
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 with hands-on experience in Python, SQL, and Power BI, delivering end-to-end analytics solutions from raw data to executive-ready dashboards. Proven ability to apply machine learning and statistical techniques to uncover actionable business insights. Comfortable working independently in remote environments with cross-functional teams.
Ziauddin University
B.S. Software Engineering · Software Engineering
August 1, 2024 – Present
Arch Technologies
Data Science Intern
March 1, 2026 – Present
India
Rhombix Technologies
Python Programmer Intern
March 1, 2025 – May 31, 2025
India
Retail Customer Sales Dashboard - End-to-End Analytics
June 22, 2026 – Present
Analyzed 3,500+ customer transactions for a retail business; cleaned raw data in Python/Pandas and authored 8+ PostgreSQL business queries to surface revenue-driving segments. Identified mid-aged males (36–55) as top spenders (under-targeted), 3,116 loyal customers outside the subscription program, and accessories as the highest-rated, highest-revenue category — each translated into a concrete strategy recommendation. Built an interactive Power BI dashboard with 5+ visuals and cross-filter slicers; delivered a client-ready business report with prioritized actions (loyalty monetization, discount guardrails, AOV-boosting bundles).
View ProjectCustomer Segmentation Using K-Means Clustering
June 22, 2026 – Present
Engineered and applied K-Means clustering on a 5K+ customer behavioral dataset; developed a segment ranking methodology producing high-value vs. at-risk customer personas. Delivered stakeholder-ready visualizations and written recommendations directly applicable to targeting, retention, and upsell strategies.
Quantium Retail Data Analytics
June 22, 2026 – Present
Executed a complete analytics workflow on retail transaction data: data ingestion, cleaning, customer segmentation, and controlled uplift testing (trial vs. control stores). Quantified a 7-10% sales lift in trial stores; delivered structured research report with visualizations and evidence-based recommendations.
Cultural Fit Analysis
The candidate's academic projects and internship experiences align well with a 'Data' target role, showcasing a breadth of skills from data cleaning and analysis to machine learning and visualization. The diversity of projects (retail sales, customer segmentation, A/B testing) indicates adaptability and a willingness to tackle different data challenges. The current internship as a Data Science Intern further strengthens the fit.
Soft Skills & Operational Fit
The candidate demonstrates good communication skills through clear project descriptions and experience. Their involvement in remote teams and use of collaboration tools like GitHub and Slack indicates an ability to work effectively in distributed environments. The project descriptions highlight a results-driven approach and the ability to present actionable findings to stakeholders.