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Let’s say we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.

Write a query to randomly sample a row from this table.

Input:

<code>big_table</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>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to randomly sample a row from a big table.

Random SQL Sample

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Experiment Validity

Apiture Salaries by Position

At Apiture, our mission is to empower financial institutions to know and serve their clients with the care of a traditional community institution at the scale, speed, and efficiency required in today's digital world. With hundreds of clients throughout the U.S., we deliver comprehensive online and mobile solutions that support banks and credit unions, ranging from small community financial institutions to new, innovative direct banks. Summary:Apiture is seeking a versatile Data Analyst to interpret complex datasets, identify trends and provide actionable insights that drive strategic decision making for Apiture and our clients. Location (Wilmington, NC, Austin, TX, Remote):We have offices in Wilmington, NC and Austin, TX and while some positions need to be office based, we will also consider remote candidates in our preferred time zones of CST/EST. Responsibilities: <ul> <li>Conduct exploratory data analysis to identify trends, patterns and anomalies </li> <li>Perform deep data mining and manipulation using SQL </li> <li>Work with clients to understand their business needs, formulate end-to-end solutions and train them to use these solutions effectively. </li><li>Deliver effective presentations of findings and recommendations by creating creative visual displays of quantitative information. </li><li>Work closely with the Application Development and Data Engineering teams to operationalize and maintain customer-facing data products. </li><li>Stay up to speed on new analytics trends, techniques, and technologies, and surface opportunities for their application. </li><li>Become a subject matter expert for the various business areas and their strategies, processes, policies, etc to have a holistic understanding of the business and how it's reflected in the data we capture. </li><li>Guiding/mentoring other analysts on best practices for analysis and data story-telling. </li><li>Organically finding insights through data exploration and business knowledge even without stakeholders explicitly asking for it. </li><li>Serve as an internal champion for the analytics team, including internal communication, asset creation. </li></ul>Requirements: <ul> <li>A bachelor's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Economics, or other related fields with emphasis on quantitative methods and solutions. </li><li>5+ years experience working in Data Science, Machine Learning, or Computer Science roles. </li><li>Excellent data visualization and presentation skills using tools like Domo, PowerBI, Tableau. </li><li>Ability to write (and refactor) robust code in Python and SQL employing best practice coding standards and documentation. </li><li>Prior experience with data platforms like Snowflake, AWS DMS, etc. </li><li>Strong people and communication skills to connect and influence both technical and non-technical audiences. </li><li>Experience in defining new measures and the translation of business goals into quantitative metrics and reporting </li></ul>Nice to Have <ul> <li>Experience in the banking industry. </li><li>Demonstrated skills in selecting the right statistical tools given a data analysis problem. </li><li>Develop, implement and improve Machine Learning algorithms to solve complex business problems. </li> <li>Build predictive models for forecasting, risk assessment and customer segmentation </li> <li>Familiarity with designing and analyzing A/B testing and other experiment types. </li><li>Demonstrated experience employing DevOps or MLOps methodologies. </li> </ul>

Apiture Interview Questions

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Apiture Interview Questions

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