Prepare for and practice interview questions from American Battery Solutions Inc..

American Battery Solutions Inc. Interview Questions

American Battery Solutions Inc. Interview Guides

Data Structures & Algorithms

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

Prime to N

Given an array and a target integer, write a function that returns the indices of two integers in the array that add up to the target integer.

Target Indices

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 digit_accumulator that returns the sum of every digit in a string

Digit Accumulator

Write a function to return the value of the nearest node that is a parent to both nodes.

Nearest Common Ancestor

Machine Learning

Interpret coefficients of logistic regression for categorical and boolean variables

Coefficients of Logistic Regression

Lasso vs Ridge

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

Bagging vs Boosting

What are some machine learning methods for building this system

FAQ Matching

How to model merchant acquisition in a new market?

Merchant Acquisition

Duplicate Rows

Write a query to get the duration in minutes of each ride longer than two hours, sorted descending

Time Difference

Write a query to find how much time each plane spent in the air each day in minutes rounded down

Total Time in Flight

Write a query that outputs a random manufacturer's name with an equal probability of selecting any name.

Uniform Car Maker

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

International e-Commerce Warehouse

Behavioral

Describing a data project and its challenges

Hurdles In Data Projects

Prioritized debt reduction, process improvement, and a focus on maintainability for fintech efficiency

Decreasing Tech Debt

How would you negotiate and resolve disagreements when a client rejects your proposed solution?

Client Solution Pushback

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

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

Your Strengths and Weaknesses

Product Sense & Metrics

How would you verify the claim that Facebook is losing young users and what test metrics would you look at

Losing Users

Google Maps Improvement

Classify companies as resilient, localized, or systemic stock-out risk, then propose three falsifiable hypotheses explaining the distribution

Out of Stock Inventory

How would you resolve slow, timing-out keyword searches across multiple database fields?

Search Timeout

American Battery Solutions Inc. is at the forefront of revolutionizing the energy storage industry, providing innovative battery solutions for automotive, industrial, and commercial applications. Our cutting-edge technology and engineering excellence are designed to meet the growing demand for sustainable energy sources.
As a company dedicated to advancing battery technology, we prioritize hiring top talent in fields ranging from engineering and research &amp; development to sales and operations. Our teams work collaboratively to push the boundaries of what's possible in the energy sector.
In this guide, we'll dive into American Battery Solutions' interview process, detailing what candidates can expect and how to prepare for each stage. We'll cover common questions, required skills, and the traits that make a perfect fit for our team. 
Join us and help shape the future of energy storage!

American Battery Solutions Inc. is at the forefront of revolutionizing the energy storage industry, providing innovative battery solutions for automotive, industrial, and commercial applications. Our cutting-edge technology and engineering excellence are designed to meet the growing demand for sustainable energy sources.

As a company dedicated to advancing battery technology, we prioritize hiring top talent in fields ranging from engineering and research & development to sales and operations. Our teams work collaboratively to push the boundaries of what's possible in the energy sector.

In this guide, we'll dive into American Battery Solutions' interview process, detailing what candidates can expect and how to prepare for each stage. We'll cover common questions, required skills, and the traits that make a perfect fit for our team. 

Join us and help shape the future of energy storage!

Overview

Say you are tasked with designing a data mart or data warehouse for a new online retailer.

How would you design the system?

Note: Sketch a star schema to explain your design.

Design a data warehouse for a new online retailer

Retailer Data Warehouse

Data Modeling

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?

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>

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/>

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

The Brackets Problem

Let’s say you work in air traffic control. You are given the table below containing information on flights between two cities.

Write a query to find out how much time, in minutes (rounded down), each plane spent in the air each day.

Note: Both cities are in the same time zone, so you do not need to worry about converting time zones.

<code>flights</code> table

Example:

Input:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>destination_location</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>source_location</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>plane_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>flight_start</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>flight_end</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>plane_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>calendar_day</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>time_in_min</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Please give <code>calendar_day</code> in the format <code>YYYY-MM-DD</code>

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

Let’s say you work at Allstate. Allstate is running <code>N</code> online ads right now. The table <code>ads</code> contains all those ads, ranked by popularity via the <code>id</code> column (e.g., the entry with <code>id = 1</code> is the most popular, etc.).

Create a subquery or common table expression named <code>top_ads</code> containing the top 3 ads (by popularity) and return the number of rows that would result from the following operations

<ol>
<li><code>ads INNER JOIN top_ads</code></li>
<li><code>ads LEFT JOIN top_ads</code></li>
<li><code>ads RIGHT JOIN top_ads</code></li>
<li><code>ads CROSS JOIN top_ads</code></li>
</ol>

Note: Please make the <code>join_type</code> column in your output have the values <code>inner_join</code>, <code>left_join</code>, etc. for each of their respective join types

Note: Please return only one query with each number in a different row

Example:

Input:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>join_type</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>number_of_rows</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Create top_ads with the top 3 ads and return the row counts for inner, left, right, and cross joins with ads

Size of Joins

Let’s say you are working at Facebook and are asked to investigate the claim that Facebook is losing young users.

<ol>
<li>How would you verify this claim?</li>
<li>What test metrics would you look at?</li>
</ol>

Let’s say you are working at Facebook and are asked to investigate the claim that Facebook is losing young users.

Pick the metric that is the least relevant for your analysis.

Let’s say you are working at Facebook and are asked to investigate the claim that Facebook is losing young users.

Pick the metric that is the least relevant for your analysis.

You work at a ride-sharing company and are given a table containing information about the rides of users.

Write a query to get the duration (in minutes) of each ride longer than two hours. Sort the results by duration in descending order.

<code>rides</code> table:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>passenger_user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>start_dt</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>end_dt</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>distance</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>ride_region</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>is_completed</code>	</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column	</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>duration_minutes</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Let’s say that you’re the PM on Google Maps.

<ol>
<li>How would you improve Google Maps?</li>

<li>What metrics would you check to see if your feature improvements are successful?</li>
</ol>

You are given a binary tree of unique positive numbers. Each node in the binary tree is represented as a dictionary with the following keys:

<ul>
<li><code>data</code>: integer value stored in the node</li>
<li><code>left</code>: reference to the left child (or <code>None</code>)</li>
<li><code>right</code>: reference to the right child (or <code>None</code>)</li>
</ul>

<pre tabindex="0" class="chroma"><code>node = {
 &#34;data&#34;: 6,
 &#34;left&#34;: {
 &#34;data&#34;: 3,
 &#34;left&#34;: {...},
 &#34;right&#34;: {...}
 },
 &#34;right&#34;: {
 &#34;data&#34;: 9,
 &#34;left&#34;: {...},
 &#34;right&#34;: {...}
 }
}
</code></pre>

Given two node values as input (<code>value1</code> and <code>value2</code>), write a function to return the value of the nearest common ancestor (lowest node in the tree that has both nodes as descendants).

Note: If one of the nodes doesn’t exist in the tree, return <code>-1</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code># Diagram of the binary tree
&#39;&#39;&#39;
 6 
 / \ 
 3 9 
 / \
 2 11
 / \
 5 8
&#39;&#39;&#39;
value1 = 8
value2 = 2
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>common_ancestor(root,value1,value2) -&gt; 3
</code></pre>

Explanation:

<ul>
<li>Ancestors of <code>8</code>: <code>11 → 3 → 6</code></li>
<li>Ancestors of <code>2</code>: <code>3 → 6</code></li>
<li>Common ancestors: <code>3</code> and <code>6</code></li>
<li>The nearest common ancestor is <code>3</code>.</li>
</ul>

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

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.

Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

Statistics

The support team at your company is trying to analyze ticketing data to improve response times. They have noticed that a significant number of tickets have no assigned agent, making it difficult to track the progress of these tickets.

Write a SQL query to count the total number of tickets, the number of tickets assigned to agents, and the number of tickets that are not assigned to any agent.

Note: Tickets that are not assigned to any agent have <code>NULL</code> in their <code>agent_id</code> field.

Example:

Input:

<code>tickets</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>issue</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>agent_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>created_at</td>
<td>TIMESTAMP</td>
</tr>

<tr>
<td>updated_at</td>
<td>TIMESTAMP</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>total_tickets</td>
<td>INTEGER</td>
</tr>

<tr>
<td>tickets_with_agent</td>
<td>INTEGER</td>
</tr>

<tr>
<td>tickets_without_agent</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Count total tickets, tickets with agent assignment, and tickets without agent assignment.

Ticket Agent Analysis

The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, usually starting with 0 and 1. It is often used in algorithm examples, and is defined by the following formula: F(n) = F(n-1) + F(n-2), with F(0) = 0 and F(1) = 1.

Your task is to implement the Fibonacci algorithm in three different methods:
1. Recursively
2. Iteratively
3. Using Memoization

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>n = 5
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>fibonacci(n) -&gt; 5
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>n = 10
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>fibonacci(n) -&gt; 55
</code></pre>

The Fibonacci sequence starts as follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55…

This question requires the implementation of the Fibonacci sequence using three different methods: recursively, iteratively, and using memoization.

Implementing the Fibonacci Sequence in Three Different Methods

Given an array and a target integer, write a function <code>sum_pair_indices</code> that returns the indices of two integers in the array that add up to the target integer. If not found, just return an empty list.

Note: Can you do it on \(O(n)\) time?

Note: Even though there could be many solutions, only one needs to be returned.

Example 1:

Input:

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

Output:

<pre tabindex="0" class="chroma"><code>def sum_pair_indices(array, target) -&gt; [0 3] or [1 2]
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>array = [3]
target = 6 
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>Do NOT return [0 0] as you can&#39;t use an index twice.
</code></pre>

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?

How would you interpret coefficients of logistic regression for categorical and boolean variables?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Given a table of <code>cars</code> with columns <code>id</code> and <code>make</code>, write a query that outputs a random manufacturer’s name with an equal probability of selecting any name.

Input:

<code>cars</code> table

<table>
<thead>
<tr>
<th><code>id</code></th>
<th><code>make</code></th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>Ford</td>
</tr>

<tr>
<td>2</td>
<td>Toyota</td>
</tr>

<tr>
<td>3</td>
<td>Toyota</td>
</tr>

<tr>
<td>4</td>
<td>Honda</td>
</tr>

<tr>
<td>5</td>
<td>Honda</td>
</tr>

<tr>
<td>6</td>
<td>Honda</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>make</code></td>
<td>Text</td>
</tr>
</tbody>
</table>

Given a <code>users</code> table, write a query to return only its duplicate rows.

Example:

Input:

<code>users</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>

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

You are given a <code>string</code> that represents some floating-point number. Write a function, <code>digit_accumulator</code>, that returns the sum of every digit in the <code>string</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>s = &#34;123.0045&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def digit_accumulator(s) -&gt; 15

Since 
1 + 2 + 3 + 0 + 0 + 4 + 5 = 15
</code></pre>

Let’s say that we want to build a chatbot system for frequently asked questions. Whenever a user writes a question, we want to return the closest answer from a list of FAQs.

What are some machine learning methods for building this system?

You’re a data analyst at a global CPG distributor that tracks daily stock availability across ~80 countries for the brands in its portfolio. The operations team wants to triage which brands are exposed to systemic supply-chain risk, which have only localized issues, and which are running clean so they know where to spend investigative cycles.

You have access to a daily inventory table:

<code>inventory_status</code>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>date</code></td>
<td>DATE</td>
<td>The day the snapshot was taken</td>
</tr>

<tr>
<td><code>country</code></td>
<td>VARCHAR</td>
<td>ISO country code where stock is held</td>
</tr>

<tr>
<td><code>company</code></td>
<td>VARCHAR</td>
<td>Brand in the portfolio</td>
</tr>

<tr>
<td><code>product</code></td>
<td>VARCHAR</td>
<td>SKU identifier</td>
</tr>

<tr>
<td><code>is_out_of_stock</code></td>
<td>BOOLEAN</td>
<td><code>TRUE</code> if the SKU was out of stock at any point that day in that country</td>
</tr>
</tbody>
</table>
Over the trailing 30 days, every company in the portfolio falls into one of three buckets:

<ol>
<li>Resilient — no stock-outs anywhere.</li>
<li>Localized risk — stock-outs occurred, but only ever within a single country.</li>
<li>Systemic risk — stock-outs occurred across multiple countries.</li>
</ol>

Given this bucket distribution, propose three business hypotheses the operations team should investigate to act on these results. For each hypothesis:

<ul>
<li>State the mechanism you think is driving the pattern.</li>
<li>Describe the follow-up analysis that would confirm or kill it.</li>
</ul>

Let’s say we’re designing a deep learning pipeline to process millions of customer support chat logs, and we want to use a Transformer encoder layer built in PyTorch to extract useful representations for downstream tasks like sentiment classification.

How would you approach building this Transformer encoder layer from scratch—what are the essential components, how would you implement them in PyTorch, and why are elements like residual connections and layer normalization critical for stable and effective training?

How would you build and justify the components of a Transformer encoder layer in PyTorch for large-scale text data?

Transformer Encoder Layer

AI & Agentic Systems

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

Let’s say you work as a data architect at Facebook.

Facebook is trying to transition their product from just doing likes on posts and comments to adding the multi-reaction under the like button.

How would you approach this problem? What would the database modifications look like?

How would you approach adding multi-reactions under the like button and what database modifications would you make

Multi-Reaction

A robot has been designed to navigate a two-dimensional 4x4 matrix by only moving forward or turning right when blocked by a wall of the matrix. Its starting position is in the top left corner of the matrix, denoted by (0,0), and the robot’s final destination is the bottom right corner.

Determine the full path of the robot before it hits the final destination or starts repeating the path.

The ‘walls’ of the matrix are either one of the four borders of the map or any block found within.

A ‘Block’ is donated by having 1 in the cell corresponding to it where an empty cell is having ‘0’.

Example 1:

<pre tabindex="0" class="chroma"><code>#Input
robot_map = [
 [0,0,0,0],[0,0,1,0],[0,1,0,0],[0,0,0,0]]

#Output
robot_path(robot_map) -&gt; [(0,0),(0,1),(0,2),(0,3),(1,3),(2,3),(3,3)]
</code></pre>

As seen in these diagrams, the robot’s path starts with this sequence of steps:

<ol>
<li>Goes forward three times and hits the wall. Turns right.</li>
<li>Goes forward three times (orientation has changed), 3. Reaches the final destination, and stops.</li>
</ol>

<img src="/s3/questions/a251a8da-2906-40de-9fe8-7f15f367fa34.png" alt="image"/>

Example 2:

<pre tabindex="0" class="chroma"><code>#Input
robot_map = [
 [0,0,1,0],[0,0,0,0],[0,1,0,0],[0,0,0,0]]

#Output
robot_path(robot_map) -&gt; [(0,0),(0,1),(1,1),(1,0)]

</code></pre>

Here, the robot moves forward one space, but hits the wall. After turning right, another wall is hit, starting a loop.

<img src="/s3/questions/34e81379-4514-472c-84a0-f31a4721f5b5.png" alt="image"/>

Determine the full path of the robot before it hits the final destination or starts repeating the path.

Walking Robot

Let’s say we’ve proposed a new analytics dashboard to a client, but after reviewing our design and data sources, the client says the solution doesn’t meet their needs and pushes back on several key features.

How would you approach the conversation to negotiate alternative solutions, and what steps would you take to ensure disagreements are handled constructively so we can still reach a successful outcome?

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

American Battery Solutions Inc. Interview Questions

American Battery Solutions Inc. Interview Guides

Overview

American Battery Solutions Inc. Interview Questions

Challenge

Discussion & Interview Experiences

Discussion & Interview Experiences