Marketing Data Analyst - Marketing Analytics Manager

Vajrala Umera Sulthana

Texas, USA 940-***-**** ************************@*****.*** LinkedIn

SUMMARY

Marketing Data Analyst with 3 years of experience analyzing marketing performance, customer acquisition, and lifecycle metrics across digital platforms. Proficient in SQL, Python, Snowflake, and BI tools, built self-serve dashboards and multi-touch attribution models that enhanced ROI visibility and reduced reporting time. Seeking to drive data-driven strategies and efficiency in a marketing analytics manager role. PROFESSIONAL EXPERIENCE

Airbnb Jul 2025 - Present

Marketing Data Analyst

• Improved the accuracy of marketing channel attribution by rebuilding the underlying data models in dbt and Snowflake, cutting daily pipeline run times by 35% (Apache Airflow) and giving growth teams actionable marketing analytics insights into CAC and ROAS across paid channels.

• Reduced ad-hoc data requests from marketing stakeholders by roughly 8–10 per week through self-service dashboard development in Apache Superset, backed by optimized Presto queries that surfaced guest acquisition and conversion trends by region.

• Quantified the contribution of each marketing touchpoint to guest bookings through multi-touch attribution analysis in Python (Pandas), reshaping how 6 paid and organic channels were credited and informing a more balanced spend allocation.

• Designed and ran A/B and incrementality tests on acquisition and re-engagement campaigns using Statsig, pairing results with funnel analysis in Amplitude to confirm a 14% lift in incremental bookings from the winning re-engagement variant.

• Owned audience segmentation for lifecycle campaigns in Braze, syncing targeted cohorts from the warehouse via Census (reverse ETL) to personalize journeys that improved 30-day guest retention by 7%. CRED Aug 2022 - May 2024

Marketing Analyst

• Queried marketing and campaign datasets using SQL and applied business analytics to track acquisition and on-site user funnels in Google Analytics 4, and built performance dashboards in Tableau, reducing weekly campaign reporting time by 6 hours and giving stakeholders faster access to key metrics.

• Extracted large-scale event data from BigQuery and performed user segmentation and cohort analysis using Python (Pandas), helping identify high-value and at-risk user groups that informed targeted outreach to a segment of 50K+ users.

• Supported A/B and multivariate experiments for in-app campaigns using Optimizely, then measured conversion lift in Mixpanel to validate top-performing variants, contributing to a 12% improvement in campaign conversion rates.

• Assisted in executing lifecycle and retention campaigns through CleverTap, monitoring push/email engagement and drop-off rates, and consolidating results in Google Sheets to improve campaign reporting consistency across teams.

• Tracked paid acquisition performance across Google Ads and Meta Ads Manager, analyzing spend, CTR, and cost-per-acquisition to flag underperforming channels, supporting a 9% reduction in cost-per-acquisition. PROJECTS

ATLAS - Cross-Channel Attribution & Media-Spend Optimization Engine

• Designed an attribution pipeline using SQL and Python to process 12M+ click and session events across six paid channels, applying Markov-chain and Shapley models to redistribute $340K in budget and improve blended ROAS by 27%

• Automated daily data refresh with dbt and Apache Airflow, reducing weekly campaign reporting from ~8 hours of manual work to under 15 minutes and powering a Looker Studio leadership dashboard

• Tech Stack: Python, BigQuery, dbt, Apache Airflow, Google Analytics 4, Looker Studio, Git HARBOR - Customer Segmentation & Lifetime-Value Forecasting Platform

• Developed an RFM + K-means segmentation across 480K customer records alongside a gradient-boosted CLV model (R 0.86), exposing high-value cohorts and lifting retargeted email conversion by 19%.

• Shipped self-serve churn-risk dashboards blending CRM engagement signals, trimming quarterly churn by 11% and saving the marketing team $120K in retention spend.

• Tech Stack: R, Snowflake, Alteryx, Azure Machine Learning, Power BI, HubSpot TECHNICAL SKILLS

• Programming & Querying: Python (Pandas), R, SQL

• Data Management & Transformation: Snowflake, BigQuery, Presto, dbt, Apache Airflow, Alteryx, Census (Reverse ETL)

• Business Intelligence & Visualization: Tableau, Power BI, Looker Studio, Apache Superset, Google Sheets

• Product, Marketing & CRM Platforms: Google Analytics 4 (GA4), Amplitude, Mixpanel, Firebase Analytics, Google Tag Manager (GTM), AppsFlyer, Adjust, Braze, CleverTap, HubSpot, Salesforce Marketing Cloud, Google Ads, Meta Ads Manager

• Experimentation, Design & Statistical Analysis: Statsig, Optimizely, A/B Testing, Multivariate Testing, Incrementality Testing, Funnel Analysis, Experiment Design

• Attribution, Segmentation & Predictive Modeling: Multi-Touch Attribution, Markov-Chain Attribution, Shapley Value Modeling, RFM Segmentation, Cohort Analysis, K-Means Clustering, Customer Lifetime Value (CLV) Forecasting, Churn Prediction, Gradient Boosting

• Machine Learning & Version Control: Azure Machine Learning, Git

• Analytics & Reporting: Marketing Analytics, Business Analytics, Product Analytics, Dashboard Development EDUCATION

University of North Texas Aug 2024 - May 2026

Master of Science, Computer Science USA

Aditya College of Engineering Aug 2020 - May 2024

Bachelor of Technology, Computer Science and Engineering India

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