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Inficon Interview Questions

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Machine Learning

Which model would perform better and why?

Booking Regression

How do we deal with the missing square footage data to construct our model

Missing Housing Data

How would we build a model to detect fraud and text customers to approve or deny fraudulent transactions

Bank Fraud Model

Rebalancing outcome probabilities for a classifier on imbalanced data.

Rebalance Probabilities

Lasso vs Ridge

Data Structures & Algorithms

Given an integer N, write a function that returns all of the prime numbers up to N

Prime to N

This problem involves identifying duplicate numbers in a list of integers. The function should return a list of the duplicate numbers.

Find Duplicate Numbers in a List

Write a function `sort_lists` to combine sorted integer lists into one sorted list without using libraries or `sort`/`sorted`

Merge N Sorted Lists

Write a function that tests whether a string of brackets is balanced.

The Brackets Problem

Write a function to find the length of the shortest transformation sequence from begin_word to end_word through the elements of word_list.

Shortest Transformation

Statistics

What are the assumptions of linear regression?

Assumptions of Linear Regression

Explain the difference between covariance and correlation and provide an example

Covariance vs Correlation

How do you detect and handle correlation between variables in linear regression, and what happens if you ignore it

Correlation in Regression

What does it mean to "bootstrap" a data set?

Bootstrapping Samples

What are the regression coefficients when regressing Y on X versus X on Y, given Y = X plus normal white noise?

Regress Y on X

Analytics

How would you present the performance of each subscription to an executive?

Analyzing Churn Behavior

Let’s say that you're in charge of an e-commerce D2C business that sells socks. What business health metrics would you care?

D2C Socks e-Commerce

Which metric should we use for late orders if the distribution is right-skewed and what does that tell us?

Late Orders

Let's say you work at Facebook and you're analyzing churn on the platform.

Retention Rate Disparity

Describing a real-world data cleaning and organization project

Data Cleaning Experiences

Supply Chain

Optimizing Supply Chain Efficiency

How would you decide on a metric and approach for worker allocation across an uneven production line?

Worker Distribution Dilemma

Which three metrics would you prioritize to evaluate supply chain efficiency at Niagara Bottling?

Supply Chain Efficiency Metrics

How would you handle a sole supplier demanding a steep price increase when resourcing isn’t an option?

Product Procurement Predicament

Given an integer <code>N</code>, write a function that returns a list of all of the prime numbers up to <code>N</code>.

Note: Return an empty list there are no prime numbers less than or equal to <code>N</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>N = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def prime_numbers(N) -&gt; [2,3]
</code></pre>

Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? 

Give an example of the tradeoffs between the two.

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

In which case would you use a bagging algorithm versus a boosting algorithm

Bagging vs Boosting

Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle it?

Describing a data project and its challenges

Hurdles In Data Projects

Behavioral

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service in addition that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

How would we build this model?

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

Let's say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

Let’s say we want to build a model to predict booking prices on Airbnb.

Between linear regression and random forest regression, which model would perform better and why?

What are the two key concepts of random forest regression?

What are the two key concepts of random forest regression?

You’re given a string that may contain the characters <code>{</code>, <code>}</code>, <code>[</code>, <code>]</code>, <code>(</code>, and <code>)</code>.

Task: Verify that the string is balanced. A balanced string is one where every opening character, <code>{</code>, <code>[</code>, or <code>(</code>, has a corresponding closing character, <code>}</code>, <code>]</code>, or <code>)</code>.

Write a function called <code>is_balanced(string: str) -&gt; bool</code> which verifies the balance of a string.

Example:

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;(())[]{}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{([(){}])()}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{}[]())&#39;) -&gt; False
</code></pre>

<hr/>

What is the difference between covariance and correlation? Provide an example.

How does random forest generate the forest? Additionally, why would we use it over other algorithms such as logistic regression?

What happens when you average the output on multiple decision trees?

What happens when you average the output on multiple decision trees?

Average Trees

How does random forest generate the forest and why use it over logistic regression

Random Forest Explanation

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years but found that around 20% of the listings are missing square footage data.

How do we deal with the missing data to construct our model?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?



Given a list of integers, identify all the duplicate values in the list. Assume that the list can contain both positive and negative numbers, and the order of the list does not matter. A number is considered a duplicate if it appears more than once in the list. Return a list of the duplicate numbers.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 2, 3, 1, 2, 3]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_duplicates(nums) -&gt; [1, 2, 3]
</code></pre>

The numbers 1, 2, and 3 all appear more than once in the list, so they are considered duplicates.

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, -1, 2, 3, 3, -1]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_duplicates(nums) -&gt; [-1, 3]
</code></pre>

The numbers -1 and 3 both appear more than once in the list, so they are considered duplicates. Note that the order of the output does not matter.

Example 3:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 2, 3, 4, 5]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_duplicates(nums) -&gt; []
</code></pre>

None of the numbers in the list appear more than once, so there are no duplicates.

Write a Python function called <code>longest_increasing_subsequence</code> that takes a list of integers as input and returns as output the length of the longest increasing subsequence in the list.

Note: An increasing subsequence is a subset of a list where the elements are in strictly increasing order. The subsequence does not have to be contiguous or unique.

<h3>Example:</h3>

Input:

<pre tabindex="0" class="chroma"><code>nums = [10, 9, 2, 5, 3, 3, 7, 101, 18]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>4
</code></pre>

Explanation:

The longest increasing subsequence is <code>[2, 3, 7, 101]</code>, for a total length of 4.

Find the longest increasing subsequence in a list of integers.

Longest Increasing Subsequence

What’s the difference between Lasso and Ridge Regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

What are the assumptions of linear regression?

Which assumption of the residuals of the standard linear regression model can not be overcome by increasing the sample size?

Regression assumptions

You’re AI engineer working on an energy forecasting system at Siemens that helps utilities predict short-term electricity demand to balance grid load and reduce outages. You train a recurrent neural network on long historical time series (weather, calendar effects, local demand signals) to forecast energy demand.

Early in training, the model appears to learn normally, but after several epochs the loss becomes highly unstable, oscillating wildly before turning into NaNs. At the same time, training slows dramatically and the model fails to recover even after restarting from recent checkpoints.

You’ve verified that the data pipeline is correct and labels are well-aligned with inputs. No changes were made to the dataset, but increasing the sequence length or learning rate makes the problem significantly worse.

How would you investigate the cause of this training instability? What signals would you look for during debugging, and how would those findings guide the changes you make to the model or training setup?

How would you investigate the cause of this training instability?

Training Instability in Neural Networks

Given a list of sorted integer lists, write a function <code>sort_lists</code> to create a combined list while maintaining sorted order without importing any libraries or using the <code>&#39;sort&#39;</code> or <code>&#39;sorted&#39;</code> functions in Python.

Example:

Input:

<pre tabindex="0" class="chroma"><code>lists = [
[1,2,3,4,5,6],
[2,5,7,8],
[3,9,10,12],
[0,1,2,8]
]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def sort_lists(lists) -&gt; [0,1,1,2,2,3,3,4,5,5,6,7,8,8,9,10,12]
</code></pre>

What are the key differences between classification models and regression models?

What is the MOST important difference between regression and classification models?

What is the MOST important difference between regression and classification models?

Classification vs Regression

Explain the key differences between classification models and regression models

Classification and Regression

Imagine you are asked to build a machine learning model to decide new loan approvals for a
financial firm. You ask the data department in the company for a subset of data to get started
working on the problem. The data includes different features about applicants such as age,
occupation, zip code, height, number of children, favorite color, etc. You decide to build
multiple machine learning models to test out different ideas before settling on the best one.

How would you explain the bias-variance tradeoff with regards to
building and choosing a model to use?

Bias vs. Variance Tradeoff

How would you handle the data preparation for building a machine learning model using imbalanced data?

Addressing imbalanced data in machine learning through carefully prepared techniques.

Data Preparation for Imbalanced Data

Let’s say that you’re training a classification model.

How would you combat overfitting when building tree-based models?

Let's say that you're training a classification model.   How would you combat overfitting when building tree-based models?

Overfit Avoidance

Let’s say we’re managing a production line for assembling electric scooters, with 10 stations where each has a different average processing time per unit (for example, Station 1 takes 5 minutes, Station 2 takes 3 minutes, and so on).

How would you determine the right metric to use for balancing worker allocation across the stations, and how would you use it to figure out how many workers each station needs?

Let’s say you work for a bank that gives out personal loans. Your co-worker develops a model that takes in customer inputs and returns if a loan should be given or not.

<ol>
<li>What kind of model did the co-worker develop? 
</li>
<li>Another co-worker thinks they have developed a better model to predict defaults on the loans. Given that personal loans are monthly installments of payments, how would you measure the difference between the two credit risk models within a timeframe? 
</li>
<li>What metrics would you track to measure the success of the new model?</li>
</ol>

What kind of model did the co-worker develop, how would you measure the difference between the two credit risk models within a timeframe, and what metrics would you track to measure the success of the new model

Loan Model

Given a string, write a function to determine if it is palindrome or not.

Note: A palindrome is a word/string that is read the same way forward as it is backward, e.g. <code>&#39;reviver&#39;</code>, <code>&#39;madam&#39;</code>, <code>&#39;deified&#39;</code> and <code>&#39;civic&#39;</code> are all palindromes, while <code>&#39;tree&#39;</code>, <code>&#39;music&#39;</code> and <code>&#39;person&#39;</code> are not palindromes.

Example:

Input:

<pre tabindex="0" class="chroma"><code>word1 = &#34;tree&#34;
word2 = &#34;radar&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def is_palindrome(word1) -&gt; False
def is_palindrome(word2) -&gt; True
</code></pre>

Given a string, write a function to determine if it is palindrome or not.

String Palindromes

Imagine you run a pizza franchise, and you run into a problem with a lot of no-shows after customers place their order.

What features would you include in a model to try to predict a no-show?

What features would you include in a model to predict a no-show

Pizza No Show

Let’s say that you’re in charge of an e-commerce D2C business that sells socks.

What business health metrics would you care about tracking on a company dashboard?

You’re given two words, <code>begin_word</code> and <code>end_word</code> which are elements of <code>word_list</code>.

Write a function <code>shortest_transformation</code> to find the length of the shortest transformation sequence from <code>begin_word</code> to <code>end_word</code> through the elements of <code>word_list</code>.

Note: Only one letter can be changed at a time and each transformed word in the list must exist inside of <code>word_list</code>.

Note: In all test cases, a path does exist between <code>begin_word</code> and <code>end_word</code>

Example:

Input:

<pre tabindex="0" class="chroma"><code>Input:
begin_word = &#34;same&#34;,
end_word = &#34;cost&#34;,
word_list = [&#34;same&#34;,&#34;came&#34;,&#34;case&#34;,&#34;cast&#34;,&#34;lost&#34;,&#34;last&#34;,&#34;cost&#34;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def shortest_transformation(begin_word, end_word, word_list) -&gt; 5
</code></pre>

Since the transformation sequence would be:

<pre tabindex="0" class="chroma"><code>&#39;same&#39; -&gt; &#39;came&#39; -&gt; &#39;case&#39; -&gt; &#39;cast&#39; -&gt; &#39;cost&#39;
</code></pre>

which is five elements long.

Write a function <code>data_stream_median</code> to calculate the new median from a stream of ordered integers and the new element which is not yet inserted into the stream.

The median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value, so the median is the mean of the two middle values.

Example:

<pre tabindex="0" class="chroma"><code>new_value = 2
stream = [1, 2, 3, 4, 5, 6]
def data_stream_median(new_value, stream): -&gt; 3
</code></pre>

Write a function data_stream_median to calculate the median from a stream of integers.

Data Stream Median

When an interviewer asks a question along the lines of:

<ul>
<li>What would your current manager say about you? What constructive criticisms might he give?</li>
<li>What are your three biggest strengths and weaknesses you have identified in yourself?</li>
</ul>

How would you respond?

When asked about your strengths in an interview, what is an effective way to respond?

When asked about your strengths in an interview, what is an effective way to respond?

Your Strengths and Weaknesses I

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Your Strengths and Weaknesses II

What do you tell an interviewer when they ask you what your strengths and weaknesses are?

Your Strengths and Weaknesses

Let’s say you work for an e-commerce company. Vendors can send products to the company’s warehouse to be listed on the website. Users are able to order any in-stock products and submit returns for refunds if they’re not satisfied.

The front end of the website includes a vendor portal that provides sales data in daily, weekly, monthly, quarterly, and yearly intervals.

The company wants to expand worldwide. They put you in charge of designing its end-to-end architecture, so you need to know what significant factors you’ll need to consider. What clarifying questions would you ask?

What kind of end-to-end architecture would you design for this company (both for ETL and reporting)?

How would you design a data warehouse for a e-commerce company looking to expand internationally?

International e-Commerce Warehouse

Let’s say we’re building a system for eBay to support multiple types of sellers: individuals, small businesses, and enterprise merchants. Each seller type shares core attributes like <code>seller_id</code> and <code>account_status</code>, but has unique features—enterprise merchants, for example, can manage up to 50 sub-accounts, while individuals have simpler profiles.

How would you decide between using composition or inheritance to model these seller types, and what trade-offs would you weigh in making your choice?

How would you decide between composition and inheritance when modeling different seller types on eBay?

Seller Type Modeling

Given two strings <code>s</code> and <code>t</code> of lengths <code>m</code> and <code>n</code> respectively, imagine you are scanning through <code>s</code>, a long string of characters, searching for something special. Somewhere inside this string may exist a small, hidden segment that perfectly satisfies a requirement defined by <code>t</code>.

Your task is to return the minimum window substring of <code>s</code> such that every character in <code>t</code> (including duplicates) is included in the window. This window must be continuous, and it must contain all required characters exactly as needed, no more and no less.

If there is no such substring — meaning the required characters cannot all be found together in any part of <code>s</code> — return the empty string <code>&#34;&#34;</code>, signaling that the search was unsuccessful.

The testcases will be generated such that the answer is unique, so once the correct window is discovered, there is no doubt that it is the only valid solution.

<h3>Example 1:</h3>

Input:

<pre tabindex="0" class="chroma"><code>s = &#34;INTERVIEWQUERYCODINGQUESTIONS&#34;, t = &#34;WING&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def minWindow(s, t) -&gt; &#34;WQUERYCODING&#34;
</code></pre>

Explanation: The minimum window substring <code>&#34;WQUERYCODING&#34;</code> includes <code>&#39;W&#39;</code>, <code>&#39;I&#39;</code>, <code>&#39;N&#39;</code>, and <code>&#39;G&#39;</code> from string <code>t</code>.

<h3>Example 2:</h3>

Input:

<pre tabindex="0" class="chroma"><code>s = &#34;a&#34;, t = &#34;aa&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def minimum_window_substring(s, t) -&gt; &#34;&#34;
</code></pre>

Explanation: Both <code>&#39;a&#39;</code>s from <code>t</code> must be included in the window. Since the largest window of <code>s</code> only has one <code>&#39;a&#39;</code>, return empty string.

<h3>Constraints:</h3>

<ul>
<li><code>m == s.length</code></li>
<li><code>n == t.length</code></li>
<li><code>1 &lt;= m, n &lt;= 10^5</code></li>
<li><code>s</code> and <code>t</code> consist of uppercase and lowercase English letters.</li>
</ul>

Hidden Substring Segment

Challenge

<h3>Job Description</h3><div>Job Description<div>Company Description INFICON is a leading provider of innovative instrumentation, critical sensor technologies, and Smart Manufacturing/Industry 4.0 software solutions that enhance productivity and quality of tools, processes, and complete factories. These analysis, measurement and control products are essential for gas leak detection in air conditioning/refrigeration and automotive manufacturing. They are vital to equipment manufacturers and end-users in the complex fabrication of semiconductors and thin film coatings for optics, flat panel displays, solar cells and industrial vacuum coating applications. Other users of our vacuum-based processes include the life sciences, research, aerospace, packaging, heat treatment, laser cutting and many other industrial processes. We also leverage our expertise in vacuum technology to provide unique, toxic chemical analysis products for emergency response, security, and environmental health and safety.Job Description INFICON is seeking a strategic and forward‑thinking Supply Chain Analytics Manager to lead the ISS Division’s supply chain analytics strategy, data architecture, KPI design, reporting, and decision-support capabilities. In this high-impact role, you will transform complex operational data into actionable insight that improves planning accuracy, optimizes inventory and working capital, enhances supplier performance, and drives operational excellence across a global high-tech manufacturing environment.Partnering closely with cross-functional leaders across planning, procurement, operations, and finance, you will build the visibility, discipline, and predictive capability needed to support faster, smarter decisions across the end-to-end supply chain. This is an opportunity to make a visible impact within an innovation-led organization where analytics is a critical driver of growth, efficiency, and customer success.Key Responsibilities:  <ul><li>Lead the ISS Division’s end-to-end supply chain analytics strategy, including KPI architecture, reporting governance, and performance measurement across planning, procurement, inventory, and logistics.</li><li>Develop and maintain executive-ready dashboards and reporting that provide visibility into on-time delivery, material availability, inventory turns, forecast accuracy, supplier performance, and procurement cost trends.</li><li>Serve as the analytical lead for the monthly SIOP process, supporting demand planning, consensus forecasting, supply-demand balancing, risk assessment, and leadership decision-making.</li><li>Build models and decision-support tools to evaluate forecast accuracy, revenue at risk, supply constraints, capacity exposure, and scenario outcomes.</li><li>Deliver procurement and supplier analytics, including spend analysis, PPV tracking, lead-time performance, supplier scorecards, and cost-reduction measurement to support sourcing and QBRs.</li><li>Build and manage data pipelines and reporting structures from SAP (MM, PP, SD, WM) and related systems, enabling scalable, automated analytics and self-service reporting through Power BI, Tableau, or SAP Analytics Cloud.</li><li>Establish and enforce data governance standards to ensure accuracy, consistency, and integrity across supply chain data sources.</li><li>Identify operational inefficiencies and drive cross-functional continuous improvement initiatives through predictive analytics, leading indicators, and digital supply chain tools.</li></ul>Qualifications Education<ul><li>Bachelor’s degree in Supply Chain, Industrial Engineering, Data Science, Operations Research, Business Analytics, or related quantitative field.</li></ul>Required Experience<ul><li>7+ years of experience in supply chain analytics, operations analytics, or business intelligence within complex manufacturing environments.</li><li>Proven success building KPI frameworks, data models, and analytics tools in multi‑product, global supply chain settings.</li><li>Strong SAP expertise across PP, MM, SD, and WM; capable of interpreting MRP logic and ERP data structures.</li><li>Advanced proficiency in data visualization (Power BI or Tableau), including data modeling and executive dashboard design.</li><li>Strong SQL and data transformation skills.  </li><li>Familiarity with forecasting methods, SIOP/S&OP analytics, capacity modeling, and inventory optimization.</li><li>Advanced Excel capability for analytical modeling and automation.</li></ul> Preferred Experience / Qualifications: <ul><li>Experience in semiconductor equipment, precision instruments, medical devices, aerospace/defense, or industrial technology.</li><li>Experience with Python or R.</li><li>Master’s degree (MBA, MS in Supply Chain, Data Science, or Engineering).</li><li>Certifications such as APICS CPIM/CSCP, SAP SCM certification, or Lean Six Sigma.</li></ul>  Additional Information The expected salary range for this position is between $90k and $130k per year. The actual compensation will be determined based on experience, location, and other factors permitted by law. In addition, INFICON employees are eligible for a profit-sharing bonus with a target of 10% as well as 401K match up to 8% (vesting schedule). A relocation package may be available for qualified candidates.<div></div>INFICON provides a dynamic work environment that promotes diversity, equity, and inclusion. Our employees experience ongoing green initiatives, flexible work hours, and a variety of health and wellness programs.INFICON’s forward-thinking approach offers countless opportunities to design, support, and manufacture a diverse product portfolio that expands globally. Our Lean and Agile work environment offers competitive compensation, relocation assistance, a discretionary bonus, and generous employee benefits; major medical, dental, health, vision, 401K, vacation and sick time, tuition reimbursement, and more!INFICON is committed to ensuring that our online application process provides an equal opportunity to all job seekers that apply without regard to race, religion, ethnicity, national origin, citizenship, gender, age, protected veteran status, disability status, genetic information, sexual orientation, or any other protected characteristic. A notice describing Federal equal employment opportunity laws is available here to reaffirm this commitment.   Any contact that would like to request a reasonable accommodation to participate in the application process should contact us.careers@inficon.com.INFICON, Inc. strictly complies with all aspects of the Export Administration Regulations ('EAR'), including those sections dealing with deemed exports to foreign nationals.</div></div>

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

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