nCino, Inc. is a rapidly growing financial technology company that specializes in providing cloud banking solutions. Positioned at the forefront of digital transformation in the financial services industry, nCino works with numerous financial institutions to streamline their processes and enhance efficiency.

Stepping into a Data Scientist role at nCino demands a robust set of analytical and technical skills. This position involves working with complex financial datasets, developing predictive models, and providing data-driven insights to drive business decisions. Interested candidates should be proficient in machine learning, statistical analysis, and possess strong programming skills in languages such as Python or R.

To assist you in your preparation, Interview Query offers a comprehensive guide to nCino's Data Scientist interview process, including typical questions and valuable tips to help you succeed. Let's delve into what you can expect and how to ace your nCino interview!

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 data scientist. 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 data scientist hiring manager stays 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 data scientist role usually is 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 data scientist roles, take-home assignments regarding product metrics, analytics, and data visualization are 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 data scientist role at Ncino.

Quick Tips For Ncino Data Scientist Interviews

• Should contain three tips for interviewing for this specific company based on interview experiences.

Example:

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Ncino interview include:

• Prepare for Technical Depth: Questions at Ncino can be quite technical, delving into machine learning, statistics, and software engineering principles. Make sure you are well-versed in these areas.
• Understand Business Applications: Ncino values how you translate technical skills into business value. Be ready to discuss how your data science skills can solve specific business problems.
• Showcase Collaborative Mindset: Ncino places a high value on teamwork and collaboration. Demonstrate your ability and willingness to work effectively within a team.

Typically, interviews at Ncino, Inc. vary by role and team, but commonly Data Scientist 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.

• Write 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.

• Write a function precision_recall to calculate precision and recall metrics from a 2-D matrix. 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 rotated 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 think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

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

• Why might the number of job applicants be decreasing while job postings remain constant? You observe that job postings per day have remained constant, but the number of applicants has been steadily 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 problems 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? 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 (O(1)) time and space? 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 and formatting changes for messy datasets? 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 and deploy 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? If you proceed, how would you evaluate the model's performance before and after deployment?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates its forest of trees. Additionally, why would you choose random forest over other algorithms like 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 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 model's accuracy and validity?

What is the average salary for a Data Scientist at Ncino, Inc.?

Q: What does Ncino, Inc. look for in a Data Scientist?
A: Ncino, Inc. seeks candidates who have strong analytical capabilities, proficiency in programming languages like Python and R, and experience with machine learning frameworks. Candidates should also possess excellent communication skills to explain data-driven insights clearly and effectively.

Q: What is the interview process for a Data Scientist role at Ncino, Inc.?
A: The interview process at Ncino typically involves an initial phone screen, followed by technical interviews assessing your coding, statistical, and machine-learning skills. Finally, there may be an onsite interview or virtual meeting to evaluate your problem-solving abilities and cultural fit.

Q: What types of projects can a Data Scientist expect to work on at Ncino, Inc.?
A: Data Scientists at Ncino work on a variety of projects ranging from developing predictive models, generating actionable business insights, to automating data processes. They collaborate closely with other teams to leverage data for product improvements and strategic decision-making.

Q: What is the company culture like at Ncino, Inc. for Data Scientists?
A: Ncino fosters a collaborative and innovative culture where Data Scientists are encouraged to take the lead on making data-driven decisions. The company values creativity, continuous learning, and encourages a strong work-life balance.

Q: How can I prepare for an interview at Ncino, Inc. for the Data Scientist role?
A: To prepare, familiarize yourself with Ncino’s products and services, practice coding problems on Interview Query, and review key machine learning concepts. Should also be ready to discuss your past projects and demonstrate how your skills align with Ncino's needs.

If you're gearing up for an exciting opportunity at Ncino, Inc. as a Data Scientist, your journey doesn't have to be a solitary endeavor. We've meticulously crafted an indispensable Ncino Interview Guide on Interview Query that delves into potential interview questions you might encounter. Additionally, explore our vast resource libraries, from software engineer to data analyst interview guides, to become thoroughly prepared for various roles within the company.

At Interview Query, we equip you with the essential tools, insights, and strategic advice to ace your interviews with confidence. Dive into our extensive company interview guides, and don't hesitate to reach out if you have any questions. Your dream job at Ncino, Inc. is within reach—let us help you make it a reality!

Good luck with your interview!