Sr. Manager, Data Science - Marketing/Media Mix Modeling

Data Scientist in San Francisco, CA , Washington, DC , Dallas, TX , Remote

Posted 2019-09-16



Oportun is a mission-driven, technology-powered provider of inclusive, affordable financial services and a certified Community Development Financial Institution (CDFI).


We seek to serve the 100 million people in the US who are shut out of the financial mainstream because they are credit invisible or are mis-scored because they have limited credit history. By lending money to hardworking, low-to-moderate income individuals, we help them move forward in their lives, demonstrate their creditworthiness, and establish the credit history they need to access new opportunities.


Since 2006, we have lent over $6.8 billion through over 3.1 million affordable small dollar loans and have helped over 730,000 people start establishing credit. In recognition of inventive approach, we were recognized by Time Magazine as one of 50 Genius Companies inventing the future.


The Bay Area News Group recognized Oportun as a Top Workplace in 2019. Come and be a part of our community of employees, partners, and customers who are devoted to expanding financial opportunity for millions. When we work together, we can make life better.



We are growing our world-class team of mission-driven, entrepreneurial Data Scientists who are passionate about broadening financial inclusion by untapping insights from credit and non-credit bureau data. Be part of the team responsible for developing and enhancing Oportun’s core intellectual property used in scoring risk for underserved consumers that often lack a traditional credit bureau score or are mis-scored by traditional credit bureaus.

In this role you will be working with large and diverse alternative data sets (i.e. data from dozens of sources including transactional, mobile, utility, other financial services, etc..) utilizing machine learning to build scores and strategies for target direct marketing campaigns (Direct Mail, Digital, etc.). You will also drive growth and optimize marketing spend across channels by leveraging alternative data to help predict which consumers would likely be interested in Oportun’s affordable, credit building products.



Develop targeting response and risk models used to market affordable and inclusive financial products to underserved consumers that often lack a traditional credit bureau score or are mis-scored by traditional credit bureaus.
Build a consumer centric marketing engine to optimize marketing spend across different channels such as direct mail, paid search, display, video, radio and affiliates.
Build scalable rapid learning pipeline leveraging advanced techniques and tools
Build end-to-end reusable pipelines from data acquisition to model output delivery
Lead initiatives to drive business value from start to finish including project planning, communication and stakeholder management
Develop actionable tools, strategies, analysis and insights that drive business outcomes and communicate findings with well organized presentations
Recommend analytic solutions to increase Oportun’s marketable universe and identify profitable prospects
Discover insights from a myriad of data sources to understand and influence consumer financial behavior
Build experimental design-based testing framework for rapid experimentation and learning
Design and build marketing data infrastructure by partnering with data and production engineering teams
Communicate and partner with third party data vendors


Master’s degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline (Bachelor’s degree with significant relevant experience will be considered)
5+ years data science experience preferably with targeting models, risk models, attribution models & Bayesian models
Digital Marketing utilizing Marketing Mix Modeling / Media Mix Modeling (MMM) experience is required
Hands on experience leveraging machine learning techniques such as Gradient Boosting, Clustering, Logistic Regression or Random Forest to solve real world problems
5+ years of hands-on experience with data extraction, cleaning, analysis and building reusable data pipelines; Proficient in SQL, Spark SQL and/or Hive
3+ years of experience in leveraging modern machine learning toolset and programming languages such as Python, SAS or Scala
Excellent written and oral communication skills
A relentless problem solver and out of the box thinker with a proven track record of driving business results in a timely manner
Strong stakeholder management and project management skills
Experience working with AWS EMR, Spark or other cloud-based platforms is a plus
Comfortable in a high-growth, fast-paced and agile environment

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Company summary

The Technology team @ Oportun is dedicated to delivering and maintaining performant, elegant, and intuitive systems to our business partners and retail customers. We provide the platform, technology services, and interfaces that have enabled Oportun to serve over 1.3M customers with over $6 billion in life-changing, responsible loans disbursed.

We work on a very unique platform, combining service-oriented platform services with sophisticated user experiences, all enabled through a best-in-class (and fun to use!) automated development infrastructure. We prove that FinTech is more fun, more challenging, and in our case, more rewarding as we build technology that changes our customers’ lives. At the corporate level, Oportun delivers a very supportive and welcoming service experience, with bilingual staff across channels, and operates more than 300 locations in CA, IL, AZ, FL, NM, TX, UT, NV & NJ, with mobile services available in MO, ID & WI.


We offer competitive salaries, bonuses, stock options, great benefits and a fully loaded laptop of your choosing. We have strong opinions about work/life balance, and seek to create a comfortable and productive environment where we can ship apps that we’re proud of and that best serve our customers. The Bay Area News Group recognized Oportun as a Top Workplace in 2019

Interview process

The interview process will differ depending on the nature of the role.

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