• Engaged with marketing stakeholders to gather requirements and translate them into detailed technical specifications for reports and dashboards.• Built, maintained, and optimized Tableau dashboards to visualize performance data across digital marketing channels, including page view data from Google Analytics and tracking of B2B leads from Salesforce.• Created ad-hoc Snowflake SQL queries to support marketing campaigns, validate data, and ensure accurate reporting on campaign effectiveness.• Fostered cross-functional relationships, promoting collaboration between marketing and data teams.• Established monitoring and alerting mechanisms for operational reports, identifying data issues and resolving them with data engineers.

Collaborated with business, product, and engineering counterparts to drive business strategy for ~250k New York Magazine subscribers. Built complex analytics models to inform SVP-level stakeholders on user engagement strategy.• Served as the subject-matter expert for subscription metrics and reporting, communicated data gaps, advocated for new metrics when needed, and worked alongside engineering and product teams to build out reporting.• Saved $20k annually by recommending to SVP-level stakeholders a migration of subscriber retention and recovery efforts to a third-party service. Exchanged data and findings directly with analysts at the service as we continued to evaluate their software.• Worked with Google Analytics click data from The Verge homepage (1.5M+ daily page views) to assess the impact of a new module on homepage click through rate. Findings were shared up to the SVP level and with The Verge publishers.Set up data models to power intricate executive-level KPI business reporting and exploratory dashboards in Looker Studio, for ~50 monthly users. Used DBT to optimize and productionize the code that served these dashboards.• Performed user acceptance testing on a new data reporting platform (Cube): built proof of concepts for analytics and business stakeholders, communicated and tracked data quality issues, and gave feedback directly to data engineers.• Affected by December 2023 layoffs in the product, design, technology, and analytics groups.

Served as the go-to analyst responsible for ad-hoc SQL queries across multiple departments, including the CEO, business operations, customer support, marketing, and sales.• Demonstrated proficiency with SQL joins, aggregations, CTEs, window functions, and query optimization techniques.• Designed, implemented, validated, and maintained data pipelines by leveraging SQL, Python, and Scala code. Created Airflow and AWS Lambda jobs to automate data pipelines that extract, transform, and load (ETL) data from various data sources (S3, REST APIs, etc.) into the data warehouse.• Provided company-wide/global metrics for social media campaigns that promoted the datasets available within the Plume suite of products.• Worked as the sole point of contact for providing personally-identifiable information (PII) stored in MongoDB databases. Performed ad-hoc analyses and data pulls for company executives to diagnose incidents in real-time and their impacts on Service Level Agreements (SLAs).• Created self-service dashboards using Tableau Desktop BI software to surface KPIs, offer live tracking of metrics, and make product data available to customer support representatives.• Corresponded directly with B2B customers (internet service providers) and provided their consumer data to them as requested.

• Extracted raw survey responses and imputed missing data for research on states of mental focus.• Visualized correlations and calculated T-test and p-values for independent groups of respondents.• Conducted regression analyses to explore relationships between demographics and states of focus.

Created five data science and analytics projects utilizing skills in data preparation, visualization, machine learning, A/B testing, and statistical modeling. Projects used Python to solve business problems related to transportation, logistics, inventory management, and risk.Technical frameworks: Python, PostgreSQL, SQL, Tableau, Jupyter Notebooks, AWS EC2, Dask, Flask, BashData Analysis: Pandas, NumPy, GeoPandas, scikit-learn, A/B Testing, Data Cleaning, ETL, Tableau, ExcelMachine Learning: Regression, Classification, Topic Modeling, Time Series, Recommendation Systems

• Independently created a "cheap flights" alert subscription service in response to a business opportunity I identified.• Leveraged Twilio, Google Sheets, Shopify, and Zapier to deliver text message alerts to an exclusive customer base.• Analyzed customer, flight, and price datasets for insights that created outstanding product value.• Single-handedly managed all operations -- including product improvement, marketing, and customer service.