Freedom Financial Network
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Data Scientist (Contractor)
at Freedom Financial Network
WHO WE ARE:
Freedom Financial Network is a family of companies that takes a people-first approach to financial services, using technology to empower consumers to overcome debt and create a brighter financial future. The company was founded in 2002 by Brad Stroh and Andrew Housser on the belief that by staying committed to helping people, you can ensure better financial outcomes for both the customer and the business. This Heart + $ philosophy still guides the vision of our growing company, which has helped millions of people find solutions for their financial needs.
What began with 2 people in a spare bedroom has now rapidly expanded to a vibrant business that employs over 2300 employees (known internally as The Freedom Family) in two locations: San Mateo, CA and Tempe, AZ. When you visit either of our offices, you’ll understand why our employees have voted us the Best Place to Work for the last several years. It’s a place where the Heart + $ philosophy continues to thrive, where we believe that success is only achieved by doing what’s right for our customers, our employees, and our communities.
In order to create brighter futures for our clients, employees, and businesses, Freedom Financial Network holds itself to four core values that have grown out of our Heart + $ philosophy: to care for everyone around us, act with integrity every time, collaborate with everybody we work with, and get better at what we do every day.
The Data Scientist Contractor will be heavily involved in executing data analysis and modeling tasks for Freedom Financial Asset Management, the lending division of the Freedom Financial Network. The overarching mandate for the Data Scientist Scientist is to execute on analytic delivery and to develop new analytic capabilities for the company. The position will essentially be to partner with leadership to execute on a broader analytic vision. Additionally, he/she may collaborate with other team members to assess and develop new analytic opportunities. This role will provide the candidate exposure and visibility into a number of strategic projects for the company, and as such, will be a high impact role within the organization.
- Become a thought leader within the organization as it pertains to analytic execution, and proactively identify opportunities to increase efficiency in analytic execution within the existing computing environment.
- Develop credit risk models using best practices in statistical modeling.
- Execute advanced analytics to support direct mail campaigns. Responsibly acquiring profitable accounts is an essential marketing function for the continued growth of the company, and the thoughtful application of advanced analytics (e.g. developing response models, calibrating response models, and conducting analysis to determine target mailing population, etc.) is essential for success.
- Evaluate and develop the analytic infrastructure that will augment the company’s analytic capabilities. This can include evaluating new technology to incorporate, or optimizing the use of existing technology within the current computing environment.
- Conduct model validation and exploratory data analysis. Develop and test hypotheses and provide insights based on results of statistical analyses. Actively participate in brainstorming sessions with broader team.
- Effectively communicating model results and limitation considerations to internal stakeholders.
Design, build, optimize and maintain predictive models and machine learning platforms
Identify opportunities for actionable use of predictive modeling / machine learning solutions
Consult with business partners to develop statistical strategy to address and influence business
Analyze data, build models and assess their quality
Design experiments and evaluate the results
Monitor model performance and make recommendations
Ad-hoc Statistical requests
Communicating results and recommendations to senior management
Identify and apply best practices and innovative solutions for next generation of predictive modeling / machine learning platforms
Our ideal candidate will be resourceful and possess very strong coding and programming skills. The credit risk functions can have far reaching consequences for the company and an attention to detail and commitment to excellence will be required. He/she will be someone that describes himself/herself, and that is described by others, as data driven, inquisitive, self-aware, culturally sensitive, thoughtful, methodical, and approachable, along with being a low maintenance and non-ego driven individual.
- 6 mos-5+ years of total experience as a Data Scientist. Financial services experience is not required, but is looked upon favorably.
- Demonstrated experience in statistical modeling and analysis. Expert level skills in SAS or Python or R.
- Demonstrated experience with qualitative and quantitative data analysis and reporting.
- Demonstrated experience working with relational databases and manipulating data from databases for statistical modeling.
- Familiarity with UNIX/LINUX environments and BASH/shell scripting is desired.
- Very strong analytical skills, combined with an ability to tie analytic results to business implications.
- A can do attitude for problem solving.
- A keen eye to spot opportunities to automate and streamline analytic processes.
- High level of comfort working within the financial services industry, as well as working within a rapidly growing environment in which change is a constant.
- An ability to work independently with limited direction but with the judgment to do so within appropriate limits of authority. Initiative to constructively, but passionately, challenge existing analytic processes.
- Expert knowledge of logistic regression, decision trees, survival analysis, design of experiment and other statistical techniques
- Expert knowledge of supervised and unsupervised machine learning techniques
- Communicating clearly and concisely to individuals from various backgrounds
- Influencing others in both verbal and written mediums
- Experience with leveraging credit bureau data for marketing targeting
- Experience working with relational databases
- Previous experience with qualitative and quantitative data analysis and reporting
- Experience with direct mail response modeling and analytics is plus
- Experience with experimental design and A/B testing
- Graduate degree in a quantitative field of study (mathematics, statistics, operations research, physics, economics, and/or financial engineering) required.
- Masters or PhD in Statistics or similar quantitative field of study (Math, Economics, Financial Engineering, Physics, Chemical Engineering, Industrial Engineering, Operations Research, etc.)
CULTURAL FIT (Our Core Values):
- Care (for everyone): We show compassion and contribute to the well-being and growth of those around us. We only pursue products that improve the financial lives of our clients.
- Act with Integrity (every time): We take the right action even when it is hard and even when no one is watching. We treat our employees, clients, and communities the way they wish to be treated.
- Get Better (every day): We innovate, iterate, and improve each day. We are creative, take thoughtful risks, and ultimately learn and recover from failures.
- COLLABORATE (with everybody): We strive to work together toward a common purpose by proactively sharing information and inviting participation. We recognize the perspective of various groups and embrace healthy, constructive debate.
Attention Agencies & Search Firms: We do not accept unsolicited candidate resumes or profiles. Please do not reach out to anyone within Freedom Financial Network (FFN) to market your services or candidates. All inquiries should be directed to Talent Acquisition only. We reserve the right to hire any candidates sent unsolicited and will not pay any fees without a contract signed by FFN’s Talent Acquisition leader.