Senior Partner Decision Scientist - job 1 of 2

As a Senior Partner Decision Scientist at Credit Karma, your primary responsibilities include collaborating with banking and FinTech partners to enhance targeting models on the Credit Karma platform. You will work closely with internal data science teams to integrate decision science models, ensuring the needs of partners are met and providing approval certainty for consumers. Building relationships with data science teams at financial institutions will also be crucial, ranging from VP-level executives to hands-on data scientists.

To be considered for the Senior Partner Decision Scientist role at Credit Karma, you will need a Bachelor's Degree in Statistics, Math, Data Analytics or a relevant quantitative discipline, along with over 5 years of experience in statistical analysis, modeling, or data analysis related to credit and underwriting. Advanced knowledge of consumer credit data and proficiency in tools like Python and SQL are essential, and experience with machine learning techniques is highly desirable.

In the role of Senior Partner Decision Scientist at Credit Karma, you'll have a direct impact on the company's success by developing and refining models that enhance the targeting of financial products. This not only improves revenue for Credit Karma but also helps partners by optimizing consumer approvals, ultimately contributing to the financial progress of our 140 million members globally.

Credit Karma provides a comprehensive benefits package for the Senior Partner Decision Scientist role, including medical and dental coverage, a retirement plan, commuter benefits, wellness perks, and substantial paid time off. Additional offerings include education perks and a unique Paid Gift Week in December, showcasing our commitment to employee well-being and professional growth.

The work culture at Credit Karma for a Senior Partner Decision Scientist is inclusive and collaborative, focusing on innovation and diversity. You’ll find a supportive environment where your contributions are valued and your voice is heard. Credit Karma has committed to advancing professional growth while fostering an atmosphere that embraces diverse perspectives and experiences among employees.

When responding to this question, highlight your relevant experiences in developing credit risk models, emphasizing specific tools and techniques you've used. Discuss how your models have impacted decision-making processes within financial institutions and how you've collaborated with cross-functional teams to enhance the overall model performance.

Be sure to mention your proficiency in statistical tools and programming languages such as Python, SQL, or R. Discuss specific projects where you applied these tools, showcasing your ability to handle large datasets and derive actionable insights that resulted in improved targeting models.

Demonstrate your interpersonal skills by discussing your approach to building relationships. Talk about your strategies for communication, collaboration, and understanding the unique needs of financial partners, emphasizing any experiences where you've successfully navigated such relationships in previous roles.

Share a specific scenario where you successfully advocated for a partner's requirements. Explain the steps you took, how you engaged with stakeholders internally, and the impact it had on the partnership and project outcomes, illustrating your ability to bridge gaps between different teams.

Discuss your validation methods in detail, such as cross-validation, A/B testing, or other statistical checks. Explain why validation is crucial in the context of credit risk modeling and how it ensures robustness and reliability in partner decision-making processes.

Highlight your commitment to professional development by mentioning any industry conferences you attend, relevant webinars or workshops, and subscriptions to financial and data science publications. This demonstrates your proactive approach to staying informed and relevant in the fast-paced financial data landscape.

Provide examples of machine learning techniques you've utilized, such as regression analysis, decision trees, or neural networks. Discuss specific projects where these techniques improved model accuracy or business outcomes, showing how you've innovatively applied data science in practical settings.

Emphasize your organizational skills and ability to prioritize tasks. Discuss frameworks or tools you use to manage your workload effectively and how you communicate with partners to set expectations while ensuring timely delivery of results.

Select a challenge that is relevant to the role, explaining your thought process and action steps. Highlight your analytical thinking and problem-solving skills while emphasizing the lessons learned as a result of overcoming that challenge.

Convey your passion for the mission of Credit Karma, its impact on financial empowerment, and how your skills align with the company’s goals. Discuss the aspects of the role that excite you the most, whether it's the collaborative environment, the innovative projects you could contribute to, or the opportunity to make a difference in people's financial lives.