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Open nowPosted 12 days ago

Marketing Analytics Manager

Twist Bioscience45 open roles

Pay
$157,000 – $198,000 a year
Where
USA - Carlsbad, CA; USA - South San Francisco, CA
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Your applicationOpen nowMarketing Analytics ManagerTwist Bioscience · USA - Carlsbad, CA; USA - South San Francisco, CA

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. Twist Bioscience postings stay open a median of 28 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 12 days ago

Twist Bioscience median: 28 days open

The posting

We are hiring a Marketing Analytics Manager to own the layer between our marketing data and the decisions our team makes - providing reliable analytics, translating insights into clear stories, and making the whole team sharper because of it.

Twist Bioscience's marketing team runs a sophisticated B2B and e-commerce funnel across Salesforce, Snowflake, and Tableau, with Segment for event tracking and a migration to Salesforce Marketing Cloud under way. Our central Business Intelligence (BI) team owns the data platform - pipelines, uptime, core fact tables - and marketing operates as a customer of that layer. This Marketing Analytics role will own the translation layer between BI's data and the decisions the business makes.

You will be the steward of marketing's own data product layer: a governed Snowflake database that already feeds lead scoring, Data Cloud, and cross-functional reporting. You'll own the data model, the metric definitions, and the delivery of insight - both through self-serve endpoints for leaders who want to query the data themselves, and through curated narratives and dashboards for those who want trusted answers in a fixed format or cadence.

There's a solid data foundation in place and a team that's actively invested in analytics. What this role adds is the person who formalizes and builds on it: completing campaign performance reporting and driving its wide adoption, supporting a migration from Marketo to Salesforce Marketing Cloud, and putting structure around things the team needs - a documented data model, a metric dictionary, automated quality checks. There's a lot of room to shape how marketing analytics works here, and the team is ready for someone to jump in and drive.

What you'll do

  • Own the data model and metric definitions. Document and maintain a single, authoritative marketing data model - funnel stages, what an MQL actually is, how campaign attribution works. Every dashboard, every report, every executive readout is grounded on it. When two dashboards show seemingly different numbers for the same metric, your job is to diagnose and either educate the team on the interpretation, or fix the underlying data model fast.
  • Deliver marketing measurement end to end. Marketing performance across the funnel, delivered as compelling stories grounded in the business, and that come with recommendations - not just numbers. You lead with the conclusion, calibrate the depth to your audience, and own the "so what."
  • Work the business problem with stakeholders. Commercial marketing, product marketing and digital marketing leaders are your primary customers. You work alongside them on why a channel is underperforming, where the funnel leaks, which segments to lean into. You bring problem-statement discipline: they describe the symptom from where it affects them, you determine the root cause.
  • Own lead quality measurement. MQL definition and lifecycle metrics, lead scoring validation, and the analysis that tells us whether marketing is delivering a pipeline that closes.
  • Build two distinct delivery channels. Self-serve: publish clear, documented endpoints and datasets so leaders who want to query the data themselves can do it accurately. Full-serve: curated visuals, recurring digests, and narrative summaries for stakeholders who want trusted, actionable answers on a fixed cadence.
  • Be the quality layer. Sanity-check self-served numbers before they reach a decision. Set up automated validation checks so interpretation or reporting problems surface fast, not after someone puts a bad number on a slide.
  • Build AI-assisted analytics tools. Maintain Marketing’s semantic layer and metric dictionary to ensure both Tableau dashboards and AI-assisted self-serve interfaces deliver standardized answers
  • Steward the marketing data product layer. Marketing owns a governed Snowflake database that feeds lead scoring, Data Cloud, and downstream reporting. You can expect extensive support from the BI team on the underlying data layers that feed this database and their interfaces to Marketing’s database, but ultimately you are its owner: you know what's in it, what depends on it, and what breaks if it changes. You work with our BI team as a knowledgeable customer of their platform, owning marketing's translation of it.
  • Represent and advocate for marketing analytics requirements as the marketing technology stack evolves - Salesforce Marketing Cloud migration, Segment instrumentation, eCommerce replatforming, and whatever comes next.

What we're looking for

Required:

  • 7-10+ years in marketing analytics, business analytics or a closely related field, including B2B funnel experience
  • Demonstrated ability to move from data to insight to recommendation - you can point to specific business decisions that changed because of your analysis
  • Strong storytelling and communication. You lead with the conclusion, calibrate to your audience, and are comfortable presenting to senior leaders. You are particularly strong at clearly communicating complex topics using data visualizations that can intuitively and quickly tell a story to busy leaders, while also being faithful representations of the underlying data. You know that a well-framed insight can often have more of a business impact than a dense dashboard.
  • Hands-on fluency with AI tools (Claude, Gemini or similar) for real analytical work - using natural language to get from data to answer, and knowing how to validate what comes back. We believe LLMs are starting to collapse the layer between a question and a dataset; we want someone who sees that shift as an advantage, not a threat
  • Working proficiency in SQL and Tableau; comfort in a cloud data warehouse (Snowflake preferred).
  • Practical fluency with marketing measurement concepts - attribution, campaign tracking, funnel and lifecycle metrics, lead scoring
  • Collaborative by default: you surface overlaps and ambiguity early rather than working around them, and you'd rather make your stakeholders self-sufficient than indispensable to them

Nice to have:

  • Life sciences, biotech or scientific-tools experience
  • E-commerce analytics, especially mixed B2B and self-serve funnels
  • Salesforce ecosystem experience - Salesforce Marketing Cloud especially; Marketo useful given our migration
  • Experience building or maintaining semantic layers, metric catalogs, data dictionaries or self-serve analytics enablement
  • Exposure to predictive modeling (churn, propensity, lead scoring) - you don't need to be a data scientist, but you should know when a model is the right answer and how to read one
  • Experience working as a customer of a central BI or data platform team - you know how to partner effectively without duplicating their work

Not required

  • Data engineering or pipeline ownership - our BI team owns that, and the operating model is well-established
  • Product analytics - a separate team owns that
  • People management - this is an IC role; you manage the function, not direct reports

The base cash compensation for this California-based role is below. In addition to base salary, this role is eligible for bonus, equity, and a generous benefits package. Final compensation amounts are determined by multiple factors, including candidate skill, experience, expertise, and location and may vary from the amount listed above. Compensation may be different in other locations.

San Francisco Bay Area Pay Range

$157,000—$198,000 USD

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