nCino, Inc. is a leading financial technology company, dedicated to transforming the banking industry with its innovative cloud banking platform. Launched in 2012 and based in Wilmington, North Carolina, nCino has been a key player in revolutionizing the digital landscape for financial institutions worldwide.

Securing a Business Intelligence (BI) position at nCino involves navigating a dynamic role that emphasizes data analysis, strategic thinking, and technological acumen. As a BI professional, you’ll be instrumental in leveraging data insights to drive business decisions and optimize banking operations through analytical tools and methodologies.

If you're aspiring to join this cutting-edge fintech firm, this guide is designed for you. Here, we’ll break down the interview process, present commonly asked questions, and offer tips to help you prepare effectively. Let’s dive in with Interview Query!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Ncino, Inc. as a Business Intelligence professional. Whether you were contacted by an Ncino recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Ncino Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Ncino Business Intelligence hiring manager might be present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Ncino Business Intelligence role is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Ncino’s data systems, ETL pipelines, and SQL queries.

In the case of Business Intelligence roles, take-home assignments regarding product metrics, analytics, and data visualization may be incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Ncino office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Business Intelligence role at Ncino.

Quick Tips For Ncino Business Intelligence Interviews

• Understand Ncino’s Products: Ncino questions are often standardized and rely heavily on situational scenarios with their products. Study Ncino’s product offerings and understand how you would personally improve or test them.
• Be Data Driven: Ncino’s Business Intelligence interviews assess how well you can provide business-driving insights with data analysis. Brush up on your knowledge of statistics and probability, given these questions can be some of the hardest to solve.
• Embody the Company Culture: Ncino values innovation, collaboration, and customer satisfaction. Practice responding to behavioral questions with answers that touch on these core values.

Typically, interviews at Ncino, Inc. vary by role and team, but commonly Business Intelligence interviews follow a fairly standardized process across these question topics.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: Determine the time complexity.

• Create a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Develop a function precision_recall to calculate precision and recall metrics. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. Write a function to search for a target value in the array. If the value is in the array, return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you suspect anything unusual about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you consider this result suspicious?

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What steps would you take if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What actions would you take to investigate and address this issue?

• Why might job applications be decreasing while job postings remain constant? You observe that the number of job postings per day has remained stable, but the number of applicants has been decreasing. What could be causing this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common issues in "messy" datasets.

• Is this a fair coin? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• How do you write a function to calculate sample variance? Write a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. Example input: test_list = [6, 7, 3, 9, 10, 15]. Example output: get_variance(test_list) -> 13.89.

• Is there anything fishy about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• How do you find the median in a list with more than 50% of the same integer in O(1) time? Given a list of sorted integers where more than 50% of the list is the same repeating integer, write a function to return the median value in (O(1)) computational time and space. Example input: li = [1,2,2]. Example output: median(li) -> 2.

• What are the drawbacks of the given student test score datasets, and how would you reformat them? You have data on student test scores in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes to make the data more useful for analysis, and describe common problems seen in "messy" datasets.

• How would you evaluate the suitability and performance of a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate whether a decision tree is the correct model for this problem? If you proceed with the decision tree, how would you evaluate its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which a random forest generates its forest. Additionally, discuss why one might choose random forest over other algorithms such as logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you use a bagging algorithm versus a boosting algorithm? Provide examples of the tradeoffs between the two.

• How would you justify using a neural network model and explain its predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier? You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to track the accuracy and validity of the model?

What is the average salary for a Business Intelligence at Ncino, Inc.?

Q: What does nCino, Inc. do?
nCino, Inc. provides cloud-based banking technology solutions. Their platform helps financial institutions streamline and enhance their operations, improve customer experience, and reduce risk.

Q: What essential skills are required for a Business Intelligence position at nCino?
You should have strong analytical skills, experience with data visualization tools (like Tableau or Power BI), proficiency in SQL, and a knack for translating data into actionable insights. Experience with cloud platforms and a background in finance or fintech is also advantageous.

Q: What is the interview process for a Business Intelligence position at nCino?
The interview process typically consists of an initial phone screen with HR, followed by one or multiple technical interviews focusing on your analytical and technical skills. The final stage may include a cultural fit interview to ensure alignment with nCino’s values and mission.

Q: How can I prepare for an interview at nCino?
To prepare for an interview at nCino, research the company and its products, understand the financial technology landscape, and brush up on your data analytics and visualization skills. Practicing common interview questions on Interview Query can boost your confidence and performance.

Q: What is the company culture like at nCino, Inc.?
nCino prides itself on a collaborative and innovative culture. They emphasize continuous learning, teamwork, and a customer-centric approach. Employees are encouraged to think creatively and contribute ideas that drive the company forward.

If you want more insights about the company, check out our main Ncino Inc. Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Ncino Inc.’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Ncino Inc. business intelligence interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!