Brand Insights, Measurement Lead

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

As a Brand Insights, Measurement Lead at Anthropic, you will strengthen the evidence that fuels our brand decisions: knowing whether marketing spend and effort is working, saying so clearly on a schedule to the people who need to hear it. Marketing Insights turns market, campaign and user data into decisions that product, marketing, comms and sales leadership can act on. You'll tell us, with data, whether awareness is turning into consideration, whether consideration is turning into pipeline, and where that chain breaks down for a given audience. This role sits at the intersection of human understanding, marketing science discipline and organizational influence.

In this role, you'll own the team's recurring measurement readouts, including the Prosumer and B2B brand health tracker studies and the metrics, headwinds and tailwinds that show up in front of business leadership and in all-hands updates, keeping them accurate, current and easy to act on. You'll partner closely with your Marketing Insights teammates, Comms and data science on the brand-health dashboard, Brand & Integrated Marketing leadership, brand data science, research vendors, and cross-functional stakeholders across Enterprise Marketing, product marketing and finance.

Responsibilities

• Own the recurring executive and all-hands readouts that put key metrics, headwinds and tailwinds in front of marketing management and the broader team
• Lead process ownership of the Prosumer and B2B brand health tracker studies, including managing the research vendor relationships that field them
• Lead coordination across Comms, Marketing and data science on the brand-health dashboard, aligning all three groups on one consistent view of the data
• Support media mix modeling, multi-touch attribution and incrementality analyses that inform how marketing budget and effort get allocated, moving the team past correlation to a defensible read on what's actually driving outcomes
• Run best-practice pre- and post-campaign analysis on individual campaigns, covering creative, channel, audience, and timing effects, and turn each read into a specific change for the next campaign
• Roll up campaign-level learnings into a recurring view for leadership: which channels, creative approaches, and audiences are outperforming over time, and where the team should adjust the playbook next
• Build audience and funnel analyses that quantify how different audiences move, and relate to each other, from awareness through consideration to conversion, and what that means for where to invest
• Audit how customer sentiment gets reported across the business and design a more efficient, consistent process
• Manage the underlying data pipelines so that recurring readouts stay reliable and don't get rebuilt from scratch each cycle
• Partner with Marketing Insights teammates to keep measurement process and research design in sync, including feeding into the Marketing Business Review scorecard process
• Develop one defensible view from first‑party behavioral data, campaign and media data, and survey or attitudinal research, being clear about what each source can and can't tell you on its own
• Present findings to non-technical audiences, including marketing leadership, enterprise sales and finance partners, translating hedged results into clear recommendations

You may be a good fit if you

• Have a strategic orientation, strong curiosity for understanding what customers and users think and how to shift perceptions, and can use that to influence business and marketing direction
• Are fluent in SQL and Python or R, and move comfortably between a quick exploratory pull and a more rigorous statistical model
• Have designed or analyzed experiments (A/B tests, holdouts, lift tests) to establish a causal effect rather than settle for a correlation, and have applied regression, segmentation or other causal‑inference methods to a real business question
• Have run campaign‑level measurement end to end, from a pre/post read on a single campaign to synthesizing learnings across multiple campaigns into a change the team acts on next time
• Have built and maintained a recurring metrics report or dashboard that executives or cross‑functional partners actually rely on, and kept it trustworthy over time
• Can turn a hedged, caveated finding into a clear recommendation a non‑technical stakeholder can act on, and know which caveat matters enough to keep in the headline
• Start an analysis by pinning down the business question and the decision it needs to serve, not the method that's most interesting to run
• Can reconcile data with no universal taxonomy across first‑party, third‑party, real‑time and survey sources
• Know when a directionally correct answer now beats a more rigorous one that arrives too late to matter
• Work well across functions, building credibility with both technical partners and non‑technical leadership
• Are excited about Anthropic's mission to develop AI that is safe and beneficial

Strong candidates may also have

• Experience with media mix modeling, multi‑touch attribution or incrementality and lift testing specifically, rather than general‑purpose analytics
• Experience advising marketing stakeholders on experimental design for live campaigns (email, paid social), or measuring marketing performance across multiple markets
• Familiarity with survey‑based quantitative research (MaxDiff, conjoint, brand and sentiment tracking) alongside behavioral and usage data
• Experience with a modern data warehouse (Snowflake, BigQuery) and a BI tool (Tableau, Looker, Power BI)
• Prior experience in marketing, growth or brand analytics specifically, rather than data science in a general or product context
• A graduate degree in statistics, economics or another quantitative field
• A career trajectory spanning BI and dashboarding, applied causal inference and experimental design, and multi‑market marketing measurement

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

$255,000 - $320,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location‑based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we’re different

We believe that the highest‑impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large‑scale research efforts. And we value impact — advancing our long‑term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest‑impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions we worked on prior to Anthropic, including: GPT‑3, Circuit‑Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.