Datadog

Staff Applied Scientist - Dashboards

Datadog$276K — $345K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • BS/MS/PhD in a scientific field or equivalent experience
  • 10+ years of relevant engineering or applied science experience
  • Proven track record of leading ML or GenAI initiatives from research to production
  • Significant experience with evaluation, experimentation, or measurement of ML systems at scale
  • Strong product mindset with the ability to drive cross-functional initiatives
  • Ability to thrive in ambiguity and make sound technical decisions

Responsibilities

  • Own the evaluation strategy for Dashboards and define optimization metrics
  • Build evaluation datasets and regression harnesses for quality assurance
  • Drive improvements in retrieval relevance and tool-selection accuracy
  • Provide technical leadership through design reviews and mentorship
  • Collaborate with engineers to enhance context efficiency

Benefits

  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Continuous professional development and career pathing opportunities
  • Inclusive company culture and employee resource groups participation
  • Global benefits, including Spring Health benefits for employees and dependents
Full Job Description
The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces-a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action - providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas.

We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number - it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success.

The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user's query can result in the agent making decisions against dozens of visualizations and data sources - both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You'll Do:
  • Own the evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics - offline and online, quality and cost, single-turn and multi-turn - that the team and the broader organization optimize against.
  • Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, and make those assets reusable by every team that is building dashboards and widgets through agents
  • Drive measurable improvements to retrieval relevance, tool-selection accuracy, and context efficiency, partnering closely with the engineers on the team.
  • Provide technical leadership across the Dashboards team and the broader organization through design reviews, working groups, and mentorship.

Who You Are:
  • You have a BS/MS/PhD in a scientific field, or equivalent experience.
  • 10+ years of relevant engineering or applied science experience, including time as a technical lead.
  • Proven track record of leading ML or GenAI initiatives in a product-driven environment, from research through production.
  • Significant experience with evaluation, experimentation, or measurement of ML systems at scale.
  • You bring a strong product mindset and are comfortable driving initiatives across cross-functional teams.
  • You thrive in ambiguity and can make sound technical calls when the path isn't yet defined.

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:
  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Continuous professional development, product training, and career pathing
  • An inclusive company culture, giving programs, and the ability to join our Community Guilds (Datadog employee resource groups)
  • Competitive global benefits and global Spring Health benefits for employees and dependents age 6+

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.

The reasonably estimated yearly salary for this role at Datadog is:

$276,000-$345,000 USD

About Datadog

Datadog is a monitoring and analytics platform for cloud-scale infrastructure and applications. The company was founded in 2010 by Olivier Pomel and Alexis Lê-Quôc and is headquartered in New York City. Datadog's platform assists organizations in improving agility, increasing efficiency, and providing end-to-end visibility across dynamic or high-scale infrastructures. The company's SaaS-based data analytics platform integrates and automates infrastructure monitoring, application performance monitoring, and log management to provide unified, real-time observability of customers' entire technology stack. Datadog's customers include Airbnb, Twilio, and The Washington Post.
Learn more about Datadog
Size
3,200 employees
Market Cap
$22.5 billion
Industry
Net Income
-$24.5 million
Founded
2010
Revenue
$603.4 million
NASDAQ

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