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Christopher Hansen personal email
As a Product Director at Spotify, 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 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.
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Senior Director, AnalyticsMongodb Oct 2024 - PresentNew York, Ny, Us -
Director Of Product ManagementSpotify Mar 2023 - Jun 2024Stockholm, Stockholm County, SeI led an R&D organization focused on building internal tooling to enable FP&A in their planning and analysis processes. Forecasting at Spotify is quite complex, and my organization's product provides FP&A analysis with the capacity to orchestrate complex workflows that start with a wide range of operational and financial inputs like user growth and prices, and then leverages dozens of models in order to generate a P&L. This tool can be leveraged both for recurring monthly and quarterly processes, and also for ad-hoc processes to support financial analysis and decision making. Finally, this tool also provides the integration capabilities for powerful ML models owned by the business, enabling FP&A to interact with these models in a no-code environment. My organization was also focused on delivering on a Financial data strategy that can not only support the planning process described above, but also financial insights and analysis processes. Our data products allow Finance users to not only easily and safely access metrics and analytical datasets, but also the underlying transaction-level details across Spotify's lines of business. Finally, my organization supported Accounting, with a strong emphasis on automation and process efficiency improvements. This means not only leveraging the data, orchestration, and integration solutions we have built for FP&A, but also leveraging new technologies like Generative AI to automate manual processes such as invoice payment. -
R&D Product Area LeadSpotify Oct 2021 - Mar 2023Stockholm, Stockholm County, SeMy organization seeks to empower Finance with advanced predictive modeling capabilities and insights to power next-gen financial decision support for Spotify. Forecasting KPIs at scale, User Lifetime Value modeling, anomaly detection and metrics monitoring, financial attribution for new initiatives and existing features in the app, and what-if analysis & simulations are some of our key areas of focus.We are also focused on building products to enable non-technical stakeholders to interact with these predictive models, breaking down technical barriers and empowering financial analysts to engage in data-driven financial decision support without the need of a data scientist or engineer.My organization consists of 50+ contributors spread across multiple teams in New York and Stockholm, and is comprised of Data Scientists, Data Engineers, Software Engineers, Product Managers, and User Research.
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Director Of Data Science: Advertising, Markets Growth, Marketing, And FinanceSpotify May 2017 - Oct 2021Stockholm, Stockholm County, SeWe are a global data science team of 30+ with expertise across disciplines and domains, and our mission is to lead sustainable growth by promoting data-informed financial decision making across businesses through unbiased, actionable insights and solutions. These solutions can range from deploying sophisticated ML models to undertaking data-driven deep dive analyses to building scalable solutions to empower financial decision making across Spotify. Focus areas include:- Producing sophisticated machine learning models to predict user growth and LTV across markets and platforms, informing strategic planning across Spotify- Providing the ads business with solutions to help build narratives that explain the value proposition of the Spotify platform via audience intelligence, audience segmentation, campaign analytics, and pricing and inventory dynamics- Analyzing all components of a given market from funnel analysis to experimentation strategy to financial results to ensure optimal resource allocation- Building statistical frameworks to understand effectiveness of marketing campaigns at a micro level, in addition to marketing spend across markets and channels at a macro level
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Svp - Global Markets AnalyticsCiti Jan 2014 - May 2017New York, New York, UsThe global markets analytics team is responsible for providing senior Markets leadership with a holistic view of the business including trading revenue, sales credits, expenses, and balance sheet.Manage a team of 4 focused on providing analytical insights, business planning and forecasting, along with data strategy, acquisition, and standardization for a $15B global business (for both Corporate and Investor Sales).The team produces daily, weekly, and monthly reports and commentary for global sales leadership, and provides client insights post key market events (such as Brexit, election, removal of Swiss Franc peg). Created new data feeds, redesigned existing database, and designed and implemented QlikView dashboards allowing senior management to view Corporate Sales activity on a global and real-time basis for the first time.Created efficiencies by merging several overlapping databases and tools into a centralized infrastructure.Worked closely with partners in Corporate Banking to ensure alignment of incentives between Corporate Banking and Markets Sales regarding efficient allocation of capital for the Corporate loan book, and developed KPIs to track performance going forward. Performed regression analyses to determine the relationship between key macroeconomic indicesand client activity for CCAR presentations to the Fed.Developed framework used to combine data sources previously incompatible with the markets client data set (e.g. balance sheet metrics) in order to drive client profitability reporting at a global Markets level.Designed and implemented governance procedures to ensure client revenue is consistent across products, and is in line with trading revenue. Significantly increased the team’s efficiency through report automation and efficient data mining. Extensive experience with developing complex data models used to forecast scenarios and identify trends. -
Vp - Sales Management Analytics & StrategyGoldman Sachs Jan 2006 - Nov 2013New York, New York, UsThe sales management team is responsible for providing the institutional sales force and sales managers with metrics and solutions to help their businesses grow and ensure proper allocation of resources.Functions include business planning, forecasting, designing tools to enhance efficiencies, developing models, ensuring data integrity and enhancing data quality across several databases. Key initiatives included client segmentation exercises, sales coverage and intensity optimization, market penetration and cross selling analysis by product and client, client / salesperson scorecard production, and tracking of KPIs for sales initiatives / growth strategies. Securities Division point person regarding implementation of Dodd-Frank regulations – extensive analysis of activity by legal entity to ensure optimal utilization in post-DF environment, prioritization of technology enhancements, coordination of client outreach to ensure proper attestation before trading, and trend analysis reporting for senior leadership.Responsible for design and implementation of attribution system to track salesperson performance, maintenance of gross credit schedules to ensure consistency of reporting across asset classes, and extensive input into client profitability models. -
Analyst - Portfolio AnalyticsBlackrock Jul 2004 - Oct 2005New York, Ny, UsResponsible for the accuracy of our risk management system for over $100 billion in assets from two prominent investment companies, on both the aggregate and individual security level.Handled ad-hoc client requests ranging from answering specific risk analytics questions, generating new reports, or explaining the functionality of our various systems.Completed several special projects, such as mining data from economic databases to run a regression analysis on TIPS securities to determine relationship between interest rate changes and activity.
Christopher Hansen Skills
Christopher Hansen Education Details
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Nyu Stern School Of BusinessAccounting And Finance
Frequently Asked Questions about Christopher Hansen
What company does Christopher Hansen work for?
Christopher Hansen works for Mongodb
What is Christopher Hansen's role at the current company?
Christopher Hansen's current role is Analytics & Data Science Leader.
What is Christopher Hansen's email address?
Christopher Hansen's email address is ch****@****ing.com
What schools did Christopher Hansen attend?
Christopher Hansen attended Nyu Stern School Of Business.
What are some of Christopher Hansen's interests?
Christopher Hansen has interest in Nba, Ghosts, Passion Pit, Grubhub, The Moon, The Killers (Band), Boo (Dog), Justice, San Antonio Spurs, Ben Folds.
What skills is Christopher Hansen known for?
Christopher Hansen has skills like Mapreduce, Python, Hive, Analysis, Start Ups, Data Analysis, Teamwork, Due Diligence, Sql, Postgresql, Data Mining, Financial Modeling.
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