Forward Deployed Engineer

Description

The company builds AI agents for marketing leaders, working alongside marketers to automate analysis, campaign planning, activation, measurement and reporting.

Customers including the NBA, Ramp, Wander, Hard Rock Stadium Group and Luxury Presence use the platform to understand their customers better and bring AI built around that understanding into their commercial teams.

The company has raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures, Future Positive, Background Capital and others. The team includes operators and investors from Citadel, Dentsu, Bridgewater, Meta Superintelligence, Growthloop, Amazon and Lazard, plus engineers and researchers from Berkeley, MIT, Stanford and Cambridge.

Each enterprise account moves from a data test to a pilot to production, and the technical win often decides the deal. The account executive owns the deal, the account manager owns the relationship and renewal, a forward deployed marketer owns the pilot outcome, and a solutions engineer runs the technical evaluation and gets standard accounts live. This role builds what the product cannot yet do.

This is not standard onboarding. You join when an account needs something built, before or after the deal closes. It is not a research role, since everything you build runs for a paying customer.

Within 90 days, you will have taken one complex account from raw data to production scoring, written down your data-readiness call, and earned the customer data team's support. Within 6 months, time-to-data-ready on complex accounts will have a tracked number that is falling, and at least one custom pipeline or model will have become a standard pattern.

Responsibilities

• Work embedded with the most complex customers, such as a pro sports team with ten years of ticketing data spread across three systems, or a brand that needs a model that does not exist yet.
• Build the custom onboarding, pipelines and models that make the product work in those environments, then bring what you learn back so future customers get it out of the box.
• Build custom ingestion and pipelines where standard onboarding does not fit, and decide whether the data is sound enough to build on, bringing messy first-party data to a state you trust.
• Build custom propensity, lookalike and scoring models using a customer's first-party data and the company's consumer graph, when the standard models fall short.
• Run scoring in production for your accounts and own its accuracy.
• When an expansion needs a capability the company lacks, scope it with the forward deployed marketer and build it.
• Turn one-off pipelines and models into patterns the data platform team can productize.
• Act as the technical voice when a customer's data team wants to understand how things actually work.
• Work with the CTO and the data science team, alongside each account's AE, forward deployed marketer and solutions engineer.
• Own time-to-data-ready and data quality on your accounts.

Requirements

• 4+ years as a data scientist or data engineer shipping to production on data-heavy work, with models that ran on real data and pipelines other people relied on.
• Strong Python and SQL, experience with dbt, an orchestrator such as Dagster or Airflow, and a cloud warehouse such as Snowflake, BigQuery or Databricks.
• Experience building predictive models such as propensity, LTV, lookalike or lead scoring, and the judgment to tell a customer when their data cannot support one.
• Comfort with messy, multi-source data, including identity resolution, entity matching, and consumer or behavioral data.
• A track record of working directly with customers or non-technical stakeholders who asked for you again.
• Based in New York City or willing to relocate, and comfortable traveling to customers.
• Nice to have: consumer data, identity graphs, adtech or martech.
• Nice to have: experiment design, including holdouts and lift measurement.
• Nice to have: forward deployed, solutions or consulting experience at a data company.
• Nice to have: sports, financial services or travel experience, where the enterprise motion is strongest.

Conditions

Base salary of $215,000 to $241,000, depending on experience.

Work in person from the office at 300 Kent Avenue in Williamsburg, Brooklyn.

Benefits

• Variable bonus targeted at 10% of base salary.
• Meaningful equity.
• Medical, dental and vision coverage.