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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

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 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

Afresh Salaries by Position

Afresh is on a mission to eliminate food waste and make fresh food accessible to all. Our first A.I.-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. With our Fresh Operating System, regional and national grocery retailers have placed $1.6 billion in produce orders across the US and we've helped our partners prevent 34 million pounds of food from going to waste. Working at Afresh represents a one-of-a-kind opportunity to have massive social impact at scale by leveraging uncommonly impactful software - we hope you'll join us! About the role: Afresh's analytics platform allows teams across the company to create reliable metrics from our disparate data sources, and to use those metrics to track internal performance, power new reporting products for our customers, and drive experiment-based decision-making. Our growing suite of reporting products help our customers understand what's happening in their stores and how to use Afresh effectively to drive down food waste. As we continue to build these products, we're looking to strengthen the analytics platform that powers them. The Data Science and Analytics team collaborates closely with every team in the company, empowering them to build products and make decisions with data. You will regularly interact with data engineers, applied scientists, data scientists, full stack engineers, and product managers. As a staff data engineer on the Data Science team, you will own the development of our analytics platform. In this role, you will evolve our data warehouse schema, solidify our transform architecture, and establish data governance patterns to serve our internal and external analytics needs. Some of your responsibilities will include: <ul><li>Improve and extend our data analytics architecture to provide reliable and accessible data for a wide range of use cases</li><li>Collaborate with engineers, product managers, and data scientists to understand their data needs, and then build extensible dimensional models and semantic layer metrics that allow for consistent and reliable insights</li><li>Evolve our existing data quality and data governance processes</li><li>Mentor and up-skill other engineers</li></ul> This is a high-impact role with ownership of highly visible projects and a lot of room to grow in your scope. Skills and experience: <ul><li>6+ years of experience as an data engineer, analytics engineer, data warehouse engineer, or a similar role.</li><li>Strong understanding of advanced concepts in SQL.</li><li>Exceptional communication and leadership skills, with a proven ability to facilitate cross-team and cross-functional collaboration and information sharing.</li><li>1+ years of experience working with SQL-driven transform libraries that support an ELT paradigm, like dbt or sqlmesh, at scale, including setting up CI/CD pipelines that ensure high quality transformations.</li><li>Expert knowledge about the differences between OLTP and OLAP database design.</li><li>Familiarity with the differences between data engineering concepts like Data Mesh, Data Lake, Data Warehouse, Data Fabric, and Data Lakehouse.</li><li>Experience with setting up a semantic layer defined with code (LookML, Cube.dev, AtScale, dbt semantic layer).</li><li>Technologies: SQL, Python, Airflow, dbt, Snowflake/Databricks/BigQuery, Spark.</li></ul> About Afresh Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices. Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals including ICML, and we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors. Fresh is the past, present, and future of our food system - the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company's values of proactivity, kindness, candor, and humility. Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law. Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, WI. However, there may be key roles that will require a candidate/employee to be local to our San Francisco, CA office. In which case this requirement will be included in the job posting details under "Skills and experience" for reference.

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