Senior Data Scientist | Growth

RampRamp·Remote(New York, NY (HQ))
Data & Analytics

WFA Digital Insight

As demand for data-driven growth strategies soars, Ramp is seeking a talented Senior Data Scientist to lead the charge. With a 16% revenue growth rate for median customers, this company is a standout in the fintech space. To succeed, candidates will need to bring a strong background in statistical modeling and machine learning, as well as the ability to communicate complex insights to cross-functional teams. Before applying, be prepared to showcase your expertise in data analysis and your passion for driving business outcomes.

Job Description

About the Role

Ramp is seeking a Senior Data Scientist to help define the analytical frameworks and strategic roadmaps for optimizing and scaling marketing investments across all brand channels.

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
  • Build attribution models and investment frameworks to inform Ramp's future brand channel investments
  • Partner closely with Martech, Business Systems, and Growth Engineering teams to augment and leverage data across first and third-party sources
  • Drive experimental design and implementation on new channels and surface areas of Ramp

How to Stand Out

  • Be prepared to walk through your experience with statistical modeling and machine learning, highlighting specific tools and techniques you've used in previous roles.
  • Develop a strong understanding of Ramp's business model and be ready to discuss how your skills can drive growth and revenue.
  • Showcase your ability to communicate complex technical concepts to non-technical stakeholders, using clear and concise language.
  • Consider creating a portfolio that highlights your experience with data analysis and visualization tools, such as Tableau or Power BI.
  • Practice discussing your experience with experimental design and A/B testing, and be prepared to provide examples of successful experiments you've led in the past.

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