Senior Manager, Marketing Data Science at Prosper
San Francisco, CA, US

Who We Are

Prosper is built on a simple idea: connect people who want to borrow money with those that have money to invest. Through Prosper, borrowers get access to fixed and low-rate loans, and investors in those loans can earn solid returns. We work to help build financial well-being for our users, enabling them to invest in each other in a way that is both financially and socially impactful. Since our launch in 2005 as the first peer-to-peer lending marketplace in the US, more than 1 million loans have been provided through the Prosper platform. We’ve helped people gain access to more than $15 billion in loans for everything from consolidating credit card debt, making home improvements, and even paying for costly medical expenses.

Backed by leading investors like Sequoia Capital, Francisco Partners, Institutional Venture Partners, and Credit Suisse NEXT Fund, our platform is developed and supported with pride in our downtown San Francisco and sunny Phoenix offices.

Our Story & Team  //   Our Blog  //  Follow us on Twitter: @ProsperLoans

What We Need

The Senior Manager of Marketing Data Science plays a pivotal role in the success of Prosper. We seek a person who is passionate about the power of data-driven modeling and its ability to drive marketing decisions. We seek a person who is experienced at using response modeling, market mix modeling and touchpoint modeling to optimize a multi-million dollar monthly marketing budget.  We seek a person who strives to improve the status quo and influence business outcome through robust statistical analysis.

The position reports to the Senior Director of Marketing & Customer Analytics, manages a team of marketing analysts, and works closely with Senior Leaders throughout the organization.  As such, the position has a tremendous amount of visibility and influence.


What You Will Do

  • Build best-in-class predictive models to drive outbound marketing programs
  • Continue to enhance and elevate our response models, uplift models, multi-touch attribution models, and other predictive marketing models
  • Recommend optimal marketing spend by channel (market mix modeling)
  • Support Marketing in determining the cadence and sequence of customer touchpoints across channels (touchpoint strategy)
  • Create test designs for a range of business questions across customer segments and marketing channels to enable improved funnel pull-through
  • Mentor junior data scientists/analysts, provide technical governance and oversight, and influence how we leverage data and modeling to drive our business to the next level

What You Will Need To Have

  • 5+ years of experience in applying data science techniques to marketing optimization
  • Experience using R/Python to manipulate large data sets
  • Expertise in response modeling, marketing mix modeling and multi-touch attribution
  • A deep understanding of statistical analysis (e.g. hypothesis testing, experimentation, regressions)
  • Comfortable and effective presenting complex data analysis, insights and recommendations to senior leadership
  • Comfortable working in a fast-moving environment with quickly changing priorities
  • Able to work independently with minimal supervision, manage several simultaneous projects, and proactively deliver key analytical projects
  • S. or Ph.D. in statistics, math, economics, computer science, information science, or another quantitative field

A Few Things to Know About Us

 We offer an excellent compensation and benefits plan, including incentive bonuses, stock options, company-paid health, dental, and vision insurance, paid vacation time, 401(k) with employer-match, fitness reimbursement, commuting reimbursement, and more! 

Prosper is committed to an inclusive and diverse workplace. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law, including the San Francisco Fair Chance Ordinance.