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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

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?

Trainual Salaries by Position

TL;DR Trainual is looking for a Senior Data Analyst to join our team. This role will be crucial in empowering our product team with the insights they need to shape our roadmap and drive strategic initiatives. Collaborating closely with product managers and leadership, you'll transform complex raw data into digestible dashboards, reports, and actionable insights that optimize our processes and inform our product's future direction. You'll manage projects, prioritize based on business value, and serve as the essential link between technical requirements and business use cases, all while utilizing advanced methodologies to push Trainual forward. (Might we say, allowing Trainual to "excel"?) So who are you? You have a knack for creative problem solving and no problem is too big or too small. SaaS environments are your jam - you can speak the product and customer lingo and have deep knowledge of metrics in each perspective function. Collaboration is your middle name (okay, that'd be weird), but you love to partner with various stakeholders and get amped up to provide them with analytics value. You're scrappy, you can be adaptable and willing to "pivot" (pun intended) on any challenge. (If you're curious how many data puns we can fit in one job description, keep reading.) Interviews for this role will start the week of November 11th. What you will own & improve: <ul> <ul><li>Data Collection and Cleaning Ensure accurate and reliable data by gathering, preprocessing, and validating data from various sources to maintain its quality and integrity. </li> <li>Data Analysis and Interpretation Utilize statistical tools and techniques to analyze data, uncover patterns, trends, and insights, and translate these findings into actionable recommendations for business improvement. </li> <li>Stakeholder Management and Communication Create clear, concise, and visually appealing reports and dashboards to communicate findings effectively to stakeholders, aiding in data-driven decision-making processes. </li></ul> </ul>What you already know: <ul> <ul><li>3-5 years of analytics experience (dare we label you a "data wizard"...) </li> <li>B2B or SaaS preferred Experience supporting Product or Finance functions </li> <li>Experience building or maintaining analytics infrastructure as the only analyst or on a small, scrappy team </li> <li>Experience configuring data movement through pipelining tools such as Fivetran or Hightouch </li> <li>Fluency in data visualization, modeling, and dashboarding </li> <li>Comfortable using SQL daily to transform data </li> <li>Able to break down complex topics into simple solutions and ideas, translating the technical for non-technical audiences (and vice versa) </li> <li>A very high sense of empowered agency. You have the capacity to take action and do so quickly. </li> <li>A nice to have would be experience in the causal modeling space (e.g. A/B Testing, Regression Analysis, Uplift Modeling, etc.) </li> </ul></ul>Our tech stack includes: <ul> <ul><li>SQL (obviously...) </li> <li>Data Transformation (dbt) </li><li>Cloud-based data warehouse (BigQuery) </li><li>Cloud-based BI tool (Omni) </li><li>Reverse-ETL (Hightouch) </li><li>Event Tracking (Hightouch) </li><li>Sales, Marketing, and CX (HubSpot) </li><li>Data Movement (Fivetran) </li><li>Version Control (GitHub) </li></ul> </ul> About the team: This role sits on our Analytics team which reports up to our CTO, Arash Tadayon. You'll report directly to Colby Schrauth (Head of Data), whereby you'll help refine and instrument the components of our data strategy, and you'll be in constant collabs with our other analytics members Will Bircher (Sr. Data Analyst), Chris Lowry (Sr. Data Analyst), and Norm Warren (Data Engineer) and various Product/CX stakeholders. Compensation: The compensation for this role is $125-145k base determined based on relevant experience to the role and industry. This role is eligible for full benefits and all the perks!

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