Christopher Hansen

About Christopher Hansen

I started my career at Spotify as a Data Science Director, and over the years I was able to influence business units across the company, and grow the team from a handful into an organization of 50+ across various disciplines, which also included Data & Software Engineering, Product, and User Research. Highlights included monetization analysis, predictive modeling, and insights self-service for the Ads business unit; causal inference, statistical analysis & modeling, and experimentation to support Marketing; analytics, insights, and experimentation to support Markets Growth; and user LTV predictive modeling and extensive Time Series Forecasting of operational and financial KPIs to support Finance. These Data Science products all contributed to Spotify\'s strategic direction, and helped further its financial decision support capabilities.I concluded my tenure at Spotify in Product Director role where I was focused on developing tooling to streamline and enhance FP & A planning and analysis processes. This included orchestrating dozens of workflows and integrating powerful machine learning models in a no-code environment, empowering financial analysts to become more effective strategic business partners. With a deep understanding of process automation and cross-functional R&D leadership, my role was instrumental in enabling non-technical stakeholders to leverage highly complex data for strategic financial decision-making.I\'m now the Sr Director of a Product & Executive (C-level) Analytics organization at MongoDB of 20+ that focuses on building durable measurement systems to track product and company performance and drive data-driven decision making across these organizations, in addition to supporting external data storytelling for investors. We leverage techniques like predictive modeling (growth and churn), time series forecasting, causal inference, statistical analysis, and experimentation to deliver clear, actionable narratives to support and accelerate decision-making. We also strongly partner with data and platform teams to drive forward a data strategy that ultimately leads to source of truth metrics for the company that originates from highly complex upstream product telemetry that is truly big data in size.

Experience

1. Senior Director, Product & Executive Analytics

   MongoDB

   Oct 2024 — Present · New York, NY, US

   I manage a Product & Executive (C-level) Analytics organization at MongoDB of 20+ that focuses on building durable measurement systems to track product and company performance and drive data-driven decision making across these organizations, in addition to supporting external data storytelling for investors. We leverage techniques like predictive modeling (growth and churn), time series forecasting, causal inference, statistical analysis, and experimentation to deliver clear, actionable narratives to support and accelerate decision-making. We also strongly partner with data and platform teams to drive forward a data strategy that ultimately leads to source of truth metrics for the company that originates from highly complex upstream product telemetry that is truly big data in size.Sample initiatives include LTV modeling, business impact analysis via causal inference techniques, propensity modeling, product experiment design and execution, revenue forecasting via time series approaches, ownership of company key metrics for internal and external reporting, predictive modeling like cluster growth/churn and org payment risk, what-if financial impact analysis, and KPI design/selection for C-suite reporting and goal tracking.

Education

• NYU Stern School of Business

  Bachelor of Science Cum Laude, Accounting and Finance

  2000 — 2004

Skills

• Market Share Analysis
• Investment Banking
• Fixed Income
• Client Analysis
• Capital Markets
• Data Visualization
• Client Profiles
• Python
• Dashboarding
• Leadership
• Tableau
• Microsoft Office
• Online Advertising
• R
• Strategy
• Financial Planning
• Sql
• Business Process Improvement
• Customer Segmentation Strategy
• Business Development
• Vba
• Project Management
• Attribution Modeling
• Excel Models
• Statistical Data Analysis
• Regression Analysis
• Financial Forecasting
• Data Mining
• Innovation Management
• Customer Relationship Management (Crm)
• Microsoft Excel
• Data Governance
• Strategic Planning
• Management
• Customer Profitability
• Financial Modeling
• Business Analysis
• Business Intelligence
• Equities
• Databases