Data Scientist

Doppel•New York, NY

7d•Hybrid

About The Position

Doppel is built to outsmart one of the great threats AI presents: mass-manufactured social engineering. Countless scams, deepfakes, and other social engineering attacks are surging across every digital channel: websites, social media, ads, encrypted messaging apps, mobile, and more. Our mission is simple but bold: make the internet a safer place by outsmarting the world’s fastest-evolving digital threats. Backed by top-tier investors and trusted by some of the world’s most recognized brands, Doppel is growing fast. If you’re driven to solve real-world problems with bold technology, we’d love to meet you. We're building the AI-native social engineering defense platform. This means we're designing scalable systems that monitor billions of domains, social media accounts, apps, dark web forums, etc., and leverage AI agents to identify and neutralize digital threats. We're hiring for a senior data scientist specifically focused on product analytics. We’re looking for a customer-obsessed data scientist who wants to have outsized impact and ownership. This role will play a significant role in shaping our roadmap. You’ll get the opportunity to join a rapidly growing company that’s making the Internet a safer place every day. We're in-person in SF/NY 3 days a week.

Requirements

4+ years of experience in data analytics, data science, or a related field.
Fluency in BigQuery/SQL and familiarity with data visualization tools like Looker Studio.
Strong foundational understanding of statistical methods, forecasting, and/or experimentation.
Experience working cross-functionally and collaborating with product, engineering, and non-technical partners.

Nice To Haves

Familiar with a language like R or Python, especially if you have experience writing Jupyter notebooks.

Responsibilities

Define the right product and customer metrics to measure success and identify new areas of opportunity.
Build scalable, self-serve dashboards to help cross-functional teams make data-driven decisions.
Create analytical models to support our product, engineering, and operations teams.
Develop forecasting models to estimate operational capacity over time, especially as we leverage AI to combat online threats.
Communicate insights clearly to technical and non-technical teams.