Senior Manager Data Science Credit Card Marketing at Sofi

The Role
The Marketing Data Science (MDS) team is looking to add a Senior Manager who will help shape Credit Card targeting decisions and strategy. The Senior Manager will be working closely with cross functional teams such as Marketing, Business Units, Compliance, Product & Finance Partners to build and grow SoFi Credit Card into a top choice for consumers to “Get Your Money Right”. 
You will be subject matter expert on Credit Card Acquisitions Strategy and have demonstrated experience in Pre-screening/Pre-approval acquisition strategy; credit bureau data; consumer profile and behavior; revenue economics; optimizing onboarding experience; and our internal customer performance and marketing datasets.  You will also contribute to building audience segmentation, models and solutions that spans across acquisition, attribution, forecasting, and budget allocation across our marketing channels.
 
What you’ll do:

Build and lead a high performing team of data scientist and institute a data-driven culture for targeted acquisition growth in Credit Card
Be a trusted advisor to our credit card marketing team and leadership on what drives marketing performance, and provide guidance on how to accelerate our growth and impact on SoFi’s long-term plan
Define and execute on a vision for the MDS CC analytics team, making the difficult tradeoffs necessary to ensure on-time deliverables and high-quality work product where it will have the highest impact
Drive the evolution of SoFi’s Credit Card acquisition strategy, including pre-screen/pre-approval marketing/offer strategy, profitable product growth, segmentation strategy and audience optimization; spanning across multiple channels; and developed in partnership with cross-functional teams
Lead analytical efforts in an unstructured environment to identify key insight that can impact efficiency and scalability of credit card acquisitions across the marketing team, including direct mail, digital, addressable/broadcast TV, and Brand
Own end-to-end Credit Card acquisition strategy, experimentation and roadmap; and manage regulatory, compliance and audit alignment associated with Credit Card marketing
Translate business goals into actionable tactics and campaigns informed by data that deliver short term results and build foundational platform for long term growth
Work with cross functional stakeholders across Marketing, Business Unit, Risk, Finance, Product and Engineering to identify strategic opportunities, measure KPIs to craft compelling stories, make data-driven recommendations, and drive informed actions. 
Synthesize data into succinct presentations that influence senior management decision making
You stay focused on what’s best for the company – sometimes that requires being flexible, other times it requires being steadfast. 

What you’ll need:

At least 3+ years in people leadership and management experience
10+ years of professional experience in business analytics (consulting to external clients and/or internal business partners), with a focus on credit card marketing, risk, business operations, or strategy
Deep expertise in Credit Card Industry, product economics and Marketing strategy is highly desired
Bachelor’s degree required (Masters preferred) in Computer Science, Math, Physics, Engineering or quantitative field. 
Ability to coach analysts to translate data into actionable business recommendations and distill findings in a way that non-technical and non-marketing teammates will understand
Proven ability to prioritize between the short-term demands and long-term needs of credit card portfolio
Track record of delivering impact. Can both develop but also help implement solutions to ambitious problems
Intellectual curiosity and aptitude to pick up new technical skills 
Ability to initiate and drive projects to completion with minimal guidance 
High EQ with ability to influence outcomes and communicate technical content to general audiences 
Strong programming skills in SQL, Python and proficiency in Tableau
Experience with experimentation and hypothesis testing
Knowledge of statistical modeling or machine learning is preferred but not a requirement
Ability to work in a dynamic, cross-functional environment, with strong attention to detail
Strong relationship building and collaborative skills