As a Marketing Analytics Specialist at Superhuman, your day-to-day work will be dynamic and highly collaborative. You will act as the source of truth for all marketing performance data, ensuring that our growth initiatives are backed by rigorous quantitative evidence.

You will spend a significant portion of your time partnering with our growth marketing managers to analyze campaign performance across paid acquisition, email marketing, content, and product-led referral loops. You will build and maintain the core dashboards that monitor our customer acquisition cost (CAC), customer lifetime value (LTV), and channel-specific conversion funnels. By identifying trends and inefficiencies in this data, you will actively influence where we allocate our marketing budget.

In addition to day-to-day reporting, you will drive strategic, long-term initiatives. This includes working closely with data engineering to design and implement robust event-tracking schemas, auditing our marketing technology stack, and running sophisticated A/B tests to optimize our sign-up flow. Your insights will not just sit in dashboards; you will regularly present strategic recommendations directly to marketing and product leadership to help guide the future of Superhuman's growth.

We are looking for analytical thinkers who are passionate about the intersection of data, marketing technology, and product growth. The ideal candidate thrives in fast-paced environments and is excited to take ownership of complex data problems.

Must-Have Skills & Experience

• Professional Experience – Typically 3+ years of experience in marketing analytics, growth analytics, or business intelligence, preferably within a B2B SaaS or fast-growing technology company.
• Advanced SQL – Exceptional SQL skills, including the ability to write complex queries, optimize performance, and work with large-scale data warehouses (e.g., Snowflake, BigQuery).
• Attribution Expertise – Deep understanding of web analytics tools (such as Google Analytics) and experience building or managing multi-touch attribution models.
• Data Visualization – Proven ability to build clear, actionable, and user-friendly dashboards using BI tools like Tableau, Looker, or Sigma.
• Communication – Strong written and verbal communication skills, with a track record of translating complex analytical insights into clear business recommendations.

Nice-to-Have Skills & Experience

• Programming Languages – Familiarity with Python or R for statistical analysis and data manipulation.
• Product-Led Growth (PLG) – Experience analyzing product-led growth loops, referral programs, and self-serve user journeys.
• B2B Marketing Funnels – Understanding of both B2C self-serve dynamics and B2B sales-assisted pipelines.

Q: How difficult is the interview process for this role? A: The process is moderately difficult to challenging. While the technical requirements (SQL, data visualization, attribution theory) are industry-standard, Superhuman places an exceptionally high bar on structured thinking, communication, and the practical application of data to real business problems.

Q: What does the take-home case study involve? A: The case study is a practical exercise designed to simulate the actual work you would do in the role. You will be given a dataset and a business prompt, and you will be asked to perform an analysis and present your findings to a panel. We look for structured methodology, clear data visualization, and actionable business recommendations.

Q: How does the team evaluate culture fit? A: We look for alignment with our core values, particularly empathy, collaborative problem-solving, and a dedication to quality. Throughout the process, we assess how you handle feedback, how you collaborate across functional lines, and how proactive you are in your communication.

Q: What is the typical timeline from the first screen to an offer? A: We aim to move candidates through the process in 3 to 4 weeks. However, depending on the depth of the panel rounds, scheduling, and reference checks, the timeline can occasionally extend to 5 to 6 weeks. We value transparency and will do our best to keep you updated at every stage.

• Master the "So What": When presenting data or answering technical questions, never stop at the metric itself. Always explain the business implication. If conversion dropped by 5%, explain what that means for revenue, acquisition costs, and what action the marketing team should take next.
• Prepare Your Stories: Use the STAR method (Situation, Task, Action, Result) to structure your behavioral answers. Focus on projects where you had to navigate ambiguity, manage difficult stakeholders, or correct an analytical error.

• Understand the Superhuman Product: Take the time to deeply understand Superhuman's product, positioning, and target audience. Think about how our product-led growth model impacts marketing analytics, and come prepared with ideas on how we can optimize our user acquisition funnel.
• Be Proactive with Communication: Our team highly values clear and proactive communication. If you have questions during the process or require clarification on the case study, do not hesitate to reach out to your recruiter. We view this proactivity as a strong positive signal.

The Marketing Analytics Specialist role at Superhuman is an exceptional opportunity to shape the growth trajectory of a category-defining product. By joining our team, you will have the platform to solve complex, high-impact data challenges, build modern measurement frameworks, and directly influence our strategic marketing investments.

To stand out, focus your preparation on mastering advanced SQL concepts, refining your marketing attribution frameworks, and practicing how you structure and present business cases. Remember, we are not just looking for someone who can pull data; we want a strategic partner who can tell a compelling story with numbers and drive actionable change.

If you are ready to take the next step and want to explore more detailed interview insights, salary benchmarks, and preparation resources, you can find comprehensive candidate tools on Dataford. We wish you the best of luck with your preparation and look forward to seeing your analytical skills in action!

The salary data shown above represents the typical compensation range for this position, including base salary and equity components. When evaluating this data, consider how your specific level of experience, location, and technical specialization align with these ranges to help guide your compensation conversations.