The GoodRX Business Intelligence interview guide, interview questions, salary data, and interview experiences.

GoodRX Business Intelligence Interview Guide

<p>Getting ready for an Business Intelligence interview at GoodRX? The GoodRX Business Intelligence interview span across 10 to 12 different question topics. In preparing for the interview:</p>
<ul>
<li>Know what skills are necessary for GoodRX Business Intelligence roles.</li>
<li>Gain insights into the Business Intelligence interview process at GoodRX.</li>
<li>Practice real GoodRX Business Intelligence interview questions.</li>
</ul>
<p>Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the GoodRX Business Intelligence interview.</p>


Getting ready for an Business Intelligence interview at GoodRX? The GoodRX Business Intelligence interview span across 10 to 12 different question topics. In preparing for the interview:

- Know what skills are necessary for GoodRX Business Intelligence roles.
- Gain insights into the Business Intelligence interview process at GoodRX.
- Practice real GoodRX Business Intelligence interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the GoodRX Business Intelligence interview.
        

Overview

GoodRX Business Intelligence Salary

<p>We've gathered this data from parsing thousands of interview experiences sourced from members.</p>

We've gathered this data from parsing thousands of interview experiences sourced from members.

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

GoodRX Business Intelligence Interview Process

<p>We’re given a table of bank transactions with three columns, <code>user_id</code>, a deposit or withdrawal value (determined if the value is positive or negative), and <code>created_at</code> time for each transaction.</p>

<p>Write a query to get the total three-day rolling average for deposits by day.</p>

<p><em>Note: Please use the format <code>&#39;%Y-%m-%d&#39;</code> for the date in the outout</em></p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>bank_transactions</code> table</p>

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

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

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

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

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

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

<tr>
<td><code>rolling_three_day</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>


Rolling Bank Transactions

<p>You’ve been asked to analyze the player’s behaviors at a gaming company.</p>

<p>Write a query to get the number of players who played between 5 and 10 games (5 and 10 excluded), and the number of players who played 10 games or more.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><strong><code>players</code></strong> table</p>

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

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

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

<tr>
<td>games_played</td>
<td>INTEGER</td>
</tr>

<tr>
<td>registered_at</td>
<td>TIMESTAMP</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

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

<tbody>
<tr>
<td>players_more_than_5_to_10_games</td>
<td>INTEGER</td>
</tr>

<tr>
<td>players_10_plus_games</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>


Obtain count of players based on games played.

Player Analysis

<p>What are the logistic and softmax functions? What is the difference between the two?</p>

<p>What makes them useful for use in logistic regression?</p>


<p>In logistic regression, how is the predicted class determined based on the logistic function?</p>


In logistic regression, how is the predicted class determined based on the logistic function?

Softmax vs Logistic II

<p>What is the key characteristic of the logistic function that makes it useful for mapping continuous values to a probability?</p>


What is the key characteristic of the logistic function that makes it useful for mapping continuous values to a probability?

Softmax vs Logistic I

What are the logistic and softmax functions? What is the difference between the two?

Softmax vs Logistic

GoodRX Business Intelligence Interview Questions

Qualifications   Master’s degree in Machine Learning, Computer Science, MIS, Mathematics, Operations Research or related field is required
7+ years of professional experience in building machine learning systems at scale
Experience in developing machine learning systems/applications on AWS, GCP or Azure
Strong programming skills in Python, Scala, Golang
Experience working with Databricks
Experience working with Apache Spark (SQL, MLlib, Streaming)
Theoretical and practical implementation experience of machine learning techniques and algorithms (at least 4 of the following): factorization machines/SVM, k-NN, Naive Bayes, Clustering, Regression (OLS, Logistic, MNL), Decision Forests/Trees/Classifiers, Linear and Nonlinear Optimization
Expertise in deep learning frameworks such as TensorFlow, PyTorch, MXNet
Comfortable with distributed systems, big data (Petabyte scale) and data-intensive systems
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
Deep understanding of data engineering practices both in modern data lakes and traditional data warehouse ecosystems that are scalable for Structured, Semi-structured and unstructured data
Strong SQL skills
Advanced understanding of data pipelines and ETL processes
Strong knowledge of System Development Life Cycle (SDLC)
Demonstrated experience in organizing work and managing multiple potentially conflicting priorities while collaborating with stakeholders across multiple functions
Strong interpersonal, presentation and communication skills
Responsibilities   Developing and implementing analytical capabilities and applications
Development of machine learning (deep learning) models and pipelines
Build production quality codes, manage and maintain the code base
Work closely with other machine learning engineers to enhance infrastructure, improve reliability and efficiency
Standardize machine learning algorithm development and deployment framework with data science workbench
Work with Data Scientists and Analysts to translate prototypes/MVPs to production deployment
Participate in developing personalization services, microservice endpoints, cross platform data products/services on Android, iOS, Web/Mobile Web
Solve complex technical issues through debugging, research and investigation
Contribute to every phase of the product development life cycle (design, development, testing, iteration, deployment)
Lead in conducting technology proof of concept projects
Gather data insights related to user behavior, product usage, audience segmentation, location intelligence, 3rd party data enrichment/append, and content consumption to drive business decisions
Benefits   The pay ranges below are shown as a guideline, and the successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, and other relevant business and organizational factors
$180,000.00 - $288,000.00
GoodRx also offers additional compensation programs such as annual cash bonuses and annual equity grants for most positions as well as generous benefits
Our great benefits offerings include medical, dental, and vision insurance, 401(k) with a company match, an ESPP, unlimited vacation, "Take Care of Yourself" days, 11 paid holidays, and 72 hours of sick leave
GoodRx also offers additional benefits like mental wellness and financial wellness programs, fertility benefits, supplemental life insurance for you and your dependents, company-paid short-term and long-term disability, and more!

#J-18808-Ljbffr

<p>Qualifications Master’s degree in Machine Learning, Computer Science, MIS, Mathematics, Operations Research or related field is required
7+ years of professional experience in building machine learning systems at scale
Experience in developing machine learning systems/applications on AWS, GCP or Azure
Strong programming skills in Python, Scala, Golang
Experience working with Databricks
Experience working with Apache Spark (SQL, MLlib, Streaming)
Theoretical and practical implementation experience of machine learning techniques and algorithms (at least 4 of the following): factorization machines/SVM, k-NN, Naive Bayes, Clustering, Regression (OLS, Logistic, MNL), Decision Forests/Trees/Classifiers, Linear and Nonlinear Optimization
Expertise in deep learning frameworks such as TensorFlow, PyTorch, MXNet
Comfortable with distributed systems, big data (Petabyte scale) and data-intensive systems
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
Deep understanding of data engineering practices both in modern data lakes and traditional data warehouse ecosystems that are scalable for Structured, Semi-structured and unstructured data
Strong SQL skills
Advanced understanding of data pipelines and ETL processes
Strong knowledge of System Development Life Cycle (SDLC)
Demonstrated experience in organizing work and managing multiple potentially conflicting priorities while collaborating with stakeholders across multiple functions
Strong interpersonal, presentation and communication skills
Responsibilities Developing and implementing analytical capabilities and applications
Development of machine learning (deep learning) models and pipelines
Build production quality codes, manage and maintain the code base
Work closely with other machine learning engineers to enhance infrastructure, improve reliability and efficiency
Standardize machine learning algorithm development and deployment framework with data science workbench
Work with Data Scientists and Analysts to translate prototypes/MVPs to production deployment
Participate in developing personalization services, microservice endpoints, cross platform data products/services on Android, iOS, Web/Mobile Web
Solve complex technical issues through debugging, research and investigation
Contribute to every phase of the product development life cycle (design, development, testing, iteration, deployment)
Lead in conducting technology proof of concept projects
Gather data insights related to user behavior, product usage, audience segmentation, location intelligence, 3rd party data enrichment/append, and content consumption to drive business decisions
Benefits The pay ranges below are shown as a guideline, and the successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, and other relevant business and organizational factors
$180,000.00 - $288,000.00
GoodRx also offers additional compensation programs such as annual cash bonuses and annual equity grants for most positions as well as generous benefits
Our great benefits offerings include medical, dental, and vision insurance, 401(k) with a company match, an ESPP, unlimited vacation, "Take Care of Yourself" days, 11 paid holidays, and 72 hours of sick leave
GoodRx also offers additional benefits like mental wellness and financial wellness programs, fertility benefits, supplemental life insurance for you and your dependents, company-paid short-term and long-term disability, and more!

#J-18808-Ljbffr</p>

GoodRX Business Intelligence Interview Guide

Overview

GoodRX Business Intelligence Salary

GoodRX Business Intelligence Interview Process

GoodRX Business Intelligence Interview Questions

GoodRX Business Intelligence Jobs