Khushmeet Arora
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North Carolina, United States
Contact Khushmeet regarding:
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Full-time jobs
Starting at
USD40/hour
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Internships
Résumé
Jobs
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- HData AnalystHue BeautyOct 2025 - Current (11 months)Ecommerce analytics startup helping brands drive conversion through user-generated video technology • Own end-to-end analytics for 90+ e-commerce brands, analyzing user behavior across monthly sessions to measure conversion lift, engagement impact, and revenue attribution from UGC video modules. • Conduct conversion funnel analysis identifying drop-off points from product page to checkout, surfacing insights that inform client optimization strategies and drive average 8-12% CVR improvements. • Analyzed and interpreted A/B experiments testing video placement, content types, and user flows, measuring statistical significance of conversion lift and engagement rate changes to validate product hypotheses. • Build customer health and engagement d
- RData AnalystReferU.ai (Early-StageJun 2025 - Aug 2025 (3 months)Legal-tech startup simplifying attorney-client matching with AI-powered recommendations • Designed and deployed a clause retrieval and knowledge graph system linking contracts, statutes, and legal opinions, enabling advanced data analysis and explainability. • Engineered a Neo4j and Qdrant architecture for data ingestion, transformation, and visualization, improving transparency and multi-hop analysis. • Partnered with stakeholders to align data pipelines and taxonomies with business needs, delivering consulting-style solutions and actionable insights. • Integrated advanced analytics workflows with LangGraph and Graphiti to provide explainable, data-driven insights supporting compliance decision-making.
- EStudent Data AnalystEDWARDS LIFESCIENCES,Jan 2025 - Jun 2025 (6 months)• Designed 4 Tableau dashboards tracking real-time quality metrics across 3 business units (THV, TMTT, SURG), reducing anomaly detection time by 20% and improving data accuracy by 25% through systematic defect code mapping. • Developed statistical correlation framework analyzing 3.2K defect reports and 47K patient complaints using chi-square testing, lift analysis, and custom Impact-Based Conversion Rate metric to quantify defect severity and inform quality improvement prioritization. • Built predictive classification model achieving 85.8% accuracy and 79.3% precision to identify high-risk Non-Conformance Reports likely to escalate into patient complaints, enabling quality teams to intervene proactively before product failures reach custome
- WAnalystWells Fargo,Jul 2022 - Jun 2024 (2 years)• Resolved 2,000+ operational incidents, safeguarding $50M+ daily trades by applying structured problem-solving and rapid root-cause analysis to minimize downtime. • Improved system throughput by 30% by leading a data engineering migration from Java MQ to Apache Kafka, strengthening enterprise pipeline performance. • Automated QA regression testing with Selenium, reducing testing effort by 40% and shortening release cycles by 2 weeks. • Boosted sprint velocity by 15% through collaboration with QA, DevOps, and Product teams, demonstrating project management and the ability to work independently. • Delivered executive-ready PowerPoint presentations on M&A analytics, effectively translating complex data into business recommendations.
Education
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Master of ScienceUniversity of California IrvineAug 2024 - Aug 2025 (1 year 1 month)- Bachelor of TechnologyCollege of Engineering PuneAug 2018 - May 2022 (3 years 10 months)
Projects (professional or personal)
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- CCredit Risk Classification (Financial Services)Jan 2025 - Mar 2025 (3 months)• Built classification models (Random Forest, Decision Tree, Logistic Regression), achieving 88% accuracy, helping financial institutions evaluate borrower risk. • Applied feature selection techniques (ANOVA, Chi-Square, Pearson correlation) to optimize inputs and improve model precision. • Delivered data-driven insights on high-risk borrower segments, enabling earlier interventions and reducing default exposure.
- CCustomer Segmentation & Behavior Analysis for Walmart (E-commerce Analytics)Jan 2025 - Mar 2025 (3 months)• Analyzed 2,000+ customer purchase records using clustering techniques (K-Means, GMM) to uncover distinct shopping behavior patterns. • Identified six actionable customer segments, delivering business insights that supported more targeted marketing campaigns and improved merchandising strategies. • Designed Python visualizations and spreadsheet-based models to present key metrics (purchase frequency, category affinity, churn risk) to stakeholders. • Translated findings into data-driven recommendations that aligned promotional strategies with customer demand, boosting campaign relevance and engagement.