Top Zest AI Interview Questions and Answers for 2023

Zest AI is a leading AI solutions provider transforming the credit industry through machine learning. With its innovative approach to making fair and transparent credit accessible, Zest AI has disrupted traditional credit scoring models.

As Zest AI continues its rapid growth, competition for jobs is fierce Preparing for the Zest AI interview process can help set you apart This comprehensive guide provides tips, example questions, and suggested answers to ace your Zest AI interview.

Overview of Zest AI

Founded in 2009, Zest AI leverages advanced artificial intelligence and machine learning to redefine credit scoring and underwriting. Their software helps lenders accurately predict credit risk increase approval rates and reduce bias.

Some key facts about Zest AI

• Headquartered in Los Angeles, CA
• Over $300 million raised in funding
• Named to Forbes AI 50 list for Most Promising Artificial Intelligence Companies in 2020
• Clients include Cardtronics, Enova Decisions, and LendingPoint

Zest AI aims to make fair and transparent credit available to everyone through better credit decisioning. Its technology analyzes thousands of traditional and non-traditional data variables to generate accurate credit scores and underwriting models. This helps lenders safely expand access to credit.

The company’s ethical AI approach has garnered much attention within the fintech industry. Zest AI is also known for its diverse and inclusive workforce.

Zest AI Company Culture

Zest AI emphasizes transparency, diversity, ethics, and a commitment to fairness in lending. The company culture is:

• Mission-driven – Employees are united by a shared vision of increasing access to fair credit. There is a sense of purpose.

• Collaborative – Cross-functional teams work closely across departments. Employees describe it as a “tight-knit” environment.

• Innovative – With a focus on cutting-edge AI, employees are encouraged to think creatively. New ideas are welcomed.

• Inclusive – Diversity and openness are core values. Zest AI has been recognized for gender diversity in its leadership.

• Supportive – Management provides mentorship opportunities and promotes growth. Employees cite excellent work-life balance.

Zest AI looks for candidates that align with its values of ethics, transparency, and innovation.

Zest AI Interview Process

The Zest AI interview process typically consists of:

1. Initial phone screen with a recruiter
2. Take-home assignment
3. Technical phone interview
4. On-site interview (multiple rounds)
5. Reference checks
6. Offer

Here is a more detailed overview of what to expect:

Phone Screen

The initial recruiter screen lasts about 30 minutes. The recruiter will assess your resume and ask questions about your background, experience, and salary expectations.

Take-Home Assignment

For technical roles, the next step is often a take-home assignment such as a coding challenge, case study, or sample work relevant to the role. This tests your skills. Allow 5-7 days to complete it.

Technical Interview

The technical phone interview focuses on your past projects, technical competencies, and problem-solving abilities. Be ready to talk through your approach on the take-home assignment.

On-site Interview

For the on-site, expect 4-5 rounds consisting of technical questions, behavioral interviews, case studies, and meetings with executives. Come prepared with thoughtful questions to ask the interviewers.

Reference & Offer

Zest AI will conduct reference checks. If successful, you will receive an offer letter with salary and benefits details. Be ready to negotiate if needed. The process can take 2-3 weeks from initial screen to offer.

Zest AI Interview Questions

Let’s look at some of the most common Zest AI interview questions and tips for crafting strong responses:

Technical Questions

Q: Explain how you have designed algorithms to solve complex problems in past roles. What was the process?

Tips: Demonstrate your approach to designing optimized algorithms. Discuss evaluating performance benchmarks, testing different algorithms, and collaborating across teams. Provide a specific example.

Q: How would you detect bias in an AI credit-decisioning model and what steps would you take to mitigate it?

Tips: Show your understanding of bias testing methods like subgroup analysis by protected classes. Discuss approaches to reducing bias such as tweaking model parameters, changing training data, or adding constraints.

Q: If you were building a model to predict loan default risk, what variables would you use as input and why?

Tips: Highlight data sources with predictive power. Explain the rationale for choosing certain variables based on their correlation with default risk. Show familiarity with traditional and alternative credit data.

Q: How have you incorporated ethics into your previous AI/ML projects?

Tips: Share examples demonstrating awareness of ethical implications – fairness, bias avoidance, interpretability, etc. Outline processes followed to ensure models met ethical standards.

Behavioral Questions

Q: Tell me about a time you had to manage an ambiguous situation. What did you do?

Tips: Share a story highlighting critical thinking, gathering data, collaborating across teams, and driving decisive action without full information.

Q: Describe a challenging situation with a client/stakeholder and how you handled it.

Tips: Choose an example demonstrating empathy, conflict resolution, and customer service skills. Explain how you identified issues and worked collaboratively to resolve the situation.

Q: When working on a team project, how do you ensure everyone’s voices are heard?

Tips: Discuss techniques for fostering inclusion like active listening, gathering input from all members, and managing dominant personalities. Share an example if possible.

Q: Tell me about a time you made a mistake. How did you handle it?

Tips: Be honest. Share an example that highlights accountability, learning, and growth. Explain the cause, how you corrected it, and processes put in place to prevent recurrence.

Case Study Questions

Q: Let’s say we wanted to launch a new credit card focused on customers with thin credit files. How would you identify this target market and quantify the opportunity?

Tips: Demonstrate strategic thinking. Ask clarifying questions. Structure your approach logically, highlighting market analysis, data sources, financial projections, and assumptions made. Communicate insights clearly.

Q: Imagine you are building an AI system to score credit applications for an auto lender. One model scores applicants as High, Medium, or Low risk. How could you evaluate and validate the model before deploying it?

Tips: Discuss evaluation methods like confusion matrices, ROC curves, Kolmogorov-Smirnov charts, etc. Explain the importance of testing on an independent dataset. Highlight bias detection. Demonstrate a methodical validation process.

Q: If you were hired as Zest’s first data scientist, how would you get ramped up and identify the highest potential areas to apply AI that would provide value?

Tips: Show strategic thinking. Discuss researching Zest’s business, meeting with stakeholders, analyzing historical data for patterns, identifying pain points, and mapping out high-value AI opportunities. Back up ideas with logical reasoning.

7 Tips to Ace Your Zest AI Interview

Here are some top tips for interview success at Zest AI:

1. Research the company – Review Zest’s website, press releases, leadership profiles, clients, and products. Know their mission and values.

2. Highlight relevant experience – Prepare stories that showcase AI/ML project experience, data analytics skills, ethics and bias prevention, and quantifiable results.

3. Brush up on AI/ML fundamentals – Study core concepts like supervised vs unsupervised learning, model evaluation metrics, regularization, etc. Be ready to discuss projects and dissertations.

4. Prepare for case studies – Practice developing structured, logical approaches to business problems. Ask clarifying questions. Communicate recommendations clearly.

5. Align with company values – Share examples that exhibit Zest’s values like diversity, transparency, innovation, and fairness in lending.

6. Prepare thoughtful questions – Ask informed questions that show your interests align with Zest’s work and mission.

7. Watch your confidence level – Be confident but humble. Know your accomplishments but focus on teamwork and learning opportunities.

Preparing for interviews takes time. But by following these tips, you can enter your Zest AI interviews assured that you have the right knowledge, experience and skills to impress the hiring team. With some practice, you can ace those Zest AI interview questions and potentially launch your career in AI and credit technology.

So do your research, believe in yourself, and get ready to show Zest AI how you can contribute to their mission of making fair and ethical credit accessible to all. You’ve got this!