Reporting to the VP of Product & Engineering, established and drove data strategy. Led team of engineers & analysts supporting Product, Sales and Marketing. Explored new methods and integration with external data sources to enhance product offerings. Continued maintenance & refinement of internally & externally delivered products. Supervised software engineering team after 2019 company reorganization. • Architected data warehouse optimized for reporting & analytics, decreasing reporting environment downtime by nearly half and speeding up query execution by up to 5x.

Reporting to the Director of Product, spearheaded advanced data analytics efforts to further develop product features and support sales goals. Supervised team of data engineers & analysts to perform custom research and analysis, producing assets used in sales, marketing, and conference presentations. Leveraged statistical and machine learning methods on product, first party, and third party data for additional insight into impact of volunteerism and community engagement. • Projects included natural language processing to extract relevant topics from academic text, word embeddings and clustering techniques to assign volunteer opportunities to one of the 17 UN Sustainable Goals, PCA on product data, and others.

Reporting to the Director of Product, built reporting infrastructure, providing customers with dynamically generated self-service insights, embedded into web-based software. Hired & supervised junior analytics staff. Performed data wrangling to restructure data from graph format to relational structure better suited for reporting & analysis. Established KPIs to better understand customer adoption, use and retention, delivered through self-service dashboards for real-time updates to Marketing, Sales and Product. Supported additional internal & customer data requests with complex ad-hoc queries.• Built self-service data delivery infrastructure for NobleHour and Collaboratory with SQL and Tibco Jaspersoft, reducing customer data extraction requests by over 90%.

Reporting to the Senior Executive Vice President, managed team of analysts and developers to extract, wrangle, and munge data. Performed analysis on big data scale datasets, wrote complex, ad-hoc queries, automated various data cleaning, munging and extraction steps, and designed models & procedures to support research. Developed & identified new data measures through requirements gathering, data mining, and data processing; assessed, documented and trained team on new processes & technologies (big data, machine learning, etc.) to refine/ensure current, scalable, consistent departmental best practices. Developed & automated data QA procedures, and supported internal & external stakeholders with product development.• Built machine learning classifier using word embeddings for previously hand-coded data, expanding categorized data to nearly 100% with 95%+ accuracy.

Reporting to the Senior Executive Vice President, oversaw team of analysts, working with clients to assess research/business needs, scope and bid projects, and ensure on-time and on-budget completion of projects while maximizing profitability. Partnered with clients to identify key consumer digital behavior metrics, providing brand interaction insights; created data visualizations, reports and products to communicate actionable insights. Collaborated cross-functionally with Sales and Engineering to translate client needs to data/technology updates. Delivered analytics research findings and insights to clients and other stakeholders, and presented at a variety of industry conferences and webinars.• Designed & implemented large-scale database processes using SQL and Python to automate data extraction from data warehouse, resulting in 5-6x reduction in processing time.

Reporting to the Senior Vice President, managed client projects throughout entire life-cycle and worked collaboratively across departments to ensure on-time and on-budget completion. Responsibilities included translating client business objectives to research objectives and designed surveys to complement data collected through Luth's proprietary data product; writing ad-hoc SQL queries to extract relevant data and insights from data warehouse; performing data analysis using various tools including Excel, Tableau, and SPSS; creatint data visualizations using Excel, PowerPoint, and Tableau; and finally creating PowerPoint presentations and presenting findings to clients.

Wrote ad-hoc queries in SQL Server and maintained an existing library of scripts and stored procedures to support various business objectives. Populated PowerPoint presentations and otherwise supported market research project deliverables.