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Jobs/New York City/Senior Data Scientist | Growth
New York City, NY

Senior Data Scientist | Growth

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $100B in annualized spend flows in and out of 50,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.

Company
Ramp
Compensation
$165,800 - $228,050
Schedule
Full-Time
Role overview

What this role actually needs.

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $100B in annualized spend flows in and out of 50,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. Responsibilities: - Employ statistical, machine learning, and econometric models on large datasets to evaluate channel performance and discern the causal impact of marketing and sales campaigns on a complex and nebulous enterprise sales cycle - Build attribution models and investment frameworks to inform Ramp’s future brand channel investments, allowing Ramp’s finance and marketing teams to scale efficiently and understand which message resonates with each audience segment at each point in the customer journey - Partner closely with Martech, Business Systems, and Growth Engineering teams to augment and leverage data across first and third-party sources, ensuring we’ve added as much context as possible to every decision we make - Drive experimental design and implementation on new channels and surface areas of Ramp, ensuring we can iterate quickly and cost-effectively, especially on marketing spend designed to build awareness, consideration, and brand equity - Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Company context: Ramp builds financial operations software with broad engineering, product, data, and infrastructure hiring across the United States and Canada.

Responsibilities

Day-to-day expectations

Ramp lists these responsibilities for the Senior Data Scientist | Growth role.

  • Employ statistical, machine learning, and econometric models on large datasets to evaluate channel performance and discern the causal impact of marketing and sales campaigns on a complex and nebulous enterprise sales cycle
  • Build attribution models and investment frameworks to inform Ramp’s future brand channel investments, allowing Ramp’s finance and marketing teams to scale efficiently and understand which message resonates with each audience segment at each point in the customer journey
  • Partner closely with Martech, Business Systems, and Growth Engineering teams to augment and leverage data across first and third-party sources, ensuring we’ve added as much context as possible to every decision we make
  • Drive experimental design and implementation on new channels and surface areas of Ramp, ensuring we can iterate quickly and cost-effectively, especially on marketing spend designed to build awareness, consideration, and brand equity
  • Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way
UpJobz market context

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Senior Data Scientist | Growth is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.

United States tech market

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Compensation read

$165,800 - $228,050 is visible before the click, so candidates can compare the role against local market expectations before applying.

Work authorization read

Current extracted signal: United States residents. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.

Location read

Hybrid roles in New York City should be compared against commute, local salary bands, and nearby employer demand.

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Watchouts

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  • Show concrete examples of succeeding in hybrid environments.
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aillmmachine-learningpythondatadbtplatformapifintechsoftware
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Source: jobs.ashbyhq.com · Source ID: 41696f51-7b29-4e12-b528-46c2f6c4f5f7 · Confidence: 93/100 · Last checked: May 7, 2026

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