Company Overview
Since 2007, BN (an Augeo company since our acquisition in 2023) has been a leader in social media tech innovation and media excellence. BN's mission has been to provide cutting-edge social advertising solutions that allow brands to maximize their brand voice on social media and drive meaningful results to their bottom line with our suite of tools:
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BN Influencer, which enables brands to transform their employees and fans into influencers to create authentic social content on the brand's behalf, all while abiding by brand safety standards.
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BN Ads, our in-house media agency that has worked with Fortune 500 clients for over 10 years.
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BN Innovate, our tech innovation hub, which partners with social platforms and brands including Amex, Meta, TikTok, X, Snapchat, and Pinterest to create technologies that sit on top of their ad buying platforms and solve business objectives with our tech expertise.
BN has offices in Rochester, NYC, Boston, Bentonville, Kansas City, and Hyderabad in addition to Augeo's offices across the country.
Description
As a Lead Data Analyst on the Data Science Team, you'll be the “analytics quarterback” on My Local Social (MLS), our store-level social marketing program spanning Walmart US, Walmart Canada, Sam's Club US, and Sam's Club Mexico. You won't just own MLS reporting and analytics; you'll be the person other teams look to when a measurement, data quality, or reporting-impact question touches MLS, and the one who sets the standards and definitions of success the rest of the program works from. You will also be the primary point of contact for day-to-day external MLS stakeholders. This role reports to the Director of BI (lead of the Data Science team).
The role has two halves. The first is ownership: the recurring client and internal reporting, the data quality standards behind it, and the database and ETL processes that feed all of it, as well as setting the standards other analysts and stakeholders follow when working with MLS data. The second is influence at a program level: establishing what success looks like for new features and pilots, making sure the right behavior is actually being tracked, validating launches, and turning what you find into recommendations the team acts on. We expect the balance to shift toward the second over time as you build trust and the reporting layer becomes more automated.
This position is expected to spend a majority of its time on program-wide measurement, coordination, and escalation rather than hands-on report building. That said, you should be ready to step into direct execution yourself when it's the highest-complexity or highest-risk item on the table.
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