Strala — Marketing Analyst

Type: Full-time | On-site | San Francisco, CA Compensation: $70,000–$100,000 + Competitive Equity Hiring count: 1 Visa sponsorship: None available Reports to: Marketing Lead

Strala is an AI-powered insurance platform that automates the entire claims process — from intake and fraud detection to settlement — helping insurers handle claims faster, more accurately, and at lower cost. It combines automation with human expertise to act like a next-generation "AI-native" claims operator, improving loss ratios, reducing manual work, and delivering better outcomes across the claims lifecycle. The company is oriented around outcomes (not activity or output) and is rebuilding claims processing with the stated ambition to process every claim in the world.

Founded: 2025 | Team size: 11–50 | Total funding: Series A (amount not stated) Industry: FinTech / Insurance Website: strala.ai Office: San Francisco, CA

• First analytical hire on a greenfield growth function: You build the measurement system the entire growth function will run on, from scratch.
• High-ownership seat: Define funnel metrics, attribution, and reporting standards that marketing, sales, and leadership all work from.
• Outcome-driven, high-standards culture: Series A momentum, competitive equity, and a mandate to do things the hard-but-correct way.

• Not provided on the role page.

Strala is building a marketing function from the ground up and needs someone who rigorously tracks performance so the team can make confident decisions about what to do next. This role owns measurement and experimentation first, with some channel execution expected — rigorously analytical first, marketer second.

• →Build and maintain marketing measurement infrastructure: UTM tracking, CRM source tagging, pipeline attribution, and channel reporting
• →Design experiments across channels with clear hypotheses, controlled setups, and honest readouts regardless of outcome
• →Report on marketing performance with intellectual honesty — what is working, what is not, and what cannot yet be concluded
• →Analyze campaign and events data to surface insights that inform budget allocation and channel prioritization
• →Support channel execution (e.g. LinkedIn campaign setup) as the operational deployment layer
• →Define and standardize funnel metrics so marketing, sales, and leadership work from the same definitions
• →Identify gaps in measurement before more money is spent on channels that can't yet be evaluated

Tech stack: Marketing analytics tools, CRM platforms, UTM tracking, pipeline attribution tooling

• 0-3 years analytical role
• Measurement infrastructure: UTMs, CRM, attribution
• Clean experimentation design
• Intellectually honest reporting
• Clear communicator to non-technical audiences
• SF 5 days, 9 to 9 in-person

• Strong analytical foundation with demonstrated rigor on small datasets. Can draw clean conclusions when data is thin.
• Intellectually honest: shows track record of reporting null results, ambiguity, and "we can't yet conclude" without overstating confidence
• Built measurement infrastructure from scratch in a prior role or strong personal project (UTMs, attribution, funnel definitions)
• Clear written and verbal communicator: can explain what data shows and does not show to a non-technical audience
• Excited about a small startup and a 9-to-9 5-day in-person commitment

• Big-company background without startup adaptation signal
• Storyteller before analyst: starts with the conclusion and finds data to support it
• Marketing operator without analytical rigor: heavy on channel execution, light on measurement chops
• Overstates confidence when data is thin
• Wants 9-to-5 or work-life-balance-first role
• Cannot work in-person 5 days a week in SF (relocation assistance available, so geography is not the blocker)

Salary$70,000–$100,000EquityCompetitive equity (no % stated)On-site policyOn-site, SF, 5 days/week, 9-to-9 in-person; relocation assistance availableVisa sponsorshipNone availableEmployment typeFull-timeLocationSan Francisco, CA

• None provided on the role page.

Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Application Review — Application review. Stage 3 — First Interview — First interview. Stage 4 — Second Interview — Second interview. Stage 5 — Case Study — Case study. Stage 6 — Case Study Review — Case study review. Stage 7 — Onsite Work Day — On-site working day. Stage 8 — Offer Extended Stage 9 — Candidate Hired — Candidate accepts and starts.

Not provided on the role page.

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• None provided on the role page.