Decagon

Decagon

Agent Data Scientist

San Francisco · Senior · Full-time

Sponsorship not specified$165k-$215kDetected 57 days ago
PythonSQLRESTData ScienceLLMsAgentic AIProduct ManagementResearch

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level II · 2×
Level I$110,3861 entry
Level II$142,4382 entries
Level III$174,5123 entries
Level IV$206,5654 entries

$9,512 more — $174,512 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $174,512 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

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About the role

  • Usually, the hard part comes from driving alignment, not the analysis itself.
  • This is a rare combination: the rigor of a strong quant, the presence of a trusted executive advisor, and the ownership of a founder.
  • This is a senior individual contributor role.

Responsibilities

  • We're building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships.
  • You own both reporting on performance and improving it, working alongside the Agent Product Managers, Agent Strategy Managers, Strategic Account Directors, and Agent Deployment Engineers on each account.
  • Own the delivery of those metrics, where transparent access to data helps reinforce the narrative we build with the customer.
  • Own improving the metrics that matter most on your accounts, from diagnosing what drives performance to designing the experiments and driving the changes that move them.
  • You operate with very little day-to-day direction, set your own priorities against a broad mandate, and bring decisions rather than questions.
  • Each customer has their own requirements for how an AI agent should be evaluated, and the narratives we build have to start there and hold up long after the decision is made.

Requirements

  • Given a question with no established right answer, you can identify the best available option and defend it.

Compensation

  • These benefits are described in more detail in Decagon's policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Benefits

  • Medical, Dental, and Vision benefits for you and your family
  • Life Insurance and Disability Benefits
  • Retirement Plan (e.g., 401K, pension)
  • Parental Leave
  • Fertility and family building benefits through Carrot
  • Monthly stipend to support your wellness, lifestyle, and work-life balance
  • Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)
  • We proudly offer the following benefits for our full-time employees:
  • We're proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.
  • These benefits are described in more detail in Decagon's policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Company info

  • When a Fortune 500 hands its customer experience to an AI agent, it is one of the largest bets the business will make that year - and enterprises of that size do not make it on a demo.
  • Data plays a central role in almost every one of those narratives, which is why Agent Data Science exists.
  • A deployment is evaluated by many stakeholders inside the customer's organization, including senior leaders, customer experience teams, and technical functions, each with their own criteria for success.
  • You own how performance is defined, measured, and demonstrated against these criteria, from translating them into metrics we operationalize and deliver, to improving the ones that are key to each evaluation.
  • You hold that from the first pre-sales evaluation through the life of the account.
  • Our team sits within Agent Product Management and focuses mostly on our largest and most complex deployments, while supporting the data needs of Decagon customers more broadly.
  • We are small relative to that surface area, which means the scope you own is very wide and exceptionally cross-functional.
  • The work compounds accordingly:
  • every metric you define on a flagship deployment becomes the default for the deals that follow, and the frameworks you build outlive any single account.
  • Demonstrating the value of our product is everyone's responsibility, not only ours.
  • So the primary leverage we create comes from making the rest of the organization better at it.
  • That is what lets us stay focused on the hardest and most novel measurement problems our customers bring us, which gives this team real influence over the long-term product roadmap.
  • Most of your time will be spent working directly with customers to establish what should be measured and then building what produces it. Usually, the hard part comes from driving alignment, not the analysis itself.
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This listing is sourced directly from Decagon's careers page and normalized into a canonical job model.