Senior Applied Scientist

Datadog

Confirmed live yesterday High trust
Hybrid

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Work type
Hybrid
Location
Posted
101 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $197k
$132k most similar roles pay here $242k

This listing doesn't post a salary. Most similar roles pay $161,250–$231,812.

Based on 240 similar postings.

Employer

About Datadog

Datadog, Inc. is an American company that provides an observability service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform.

Datadog currently has 266 open roles on FindRole.

Listed pay typically runs $161,000–$205,000 across 138 roles with salary data.

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At a glance

TL;DR · Senior Applied Scientist

As a Senior Applied Scientist on the Applied AI team, you will design, build, and scale machine learning powered features within the platform. You will work closely with engineering and product partners to research and benchmark algorithms, develop production data pipelines, and monitor models and infrastructure. Your daily responsibilities include analyzing high volumes of streaming data to solve problems like anomaly detection, error outliers, and faulty deployment analysis. The role requires expertise in machine learning algorithms, statistical techniques, and building scalable systems for large datasets. You will also participate in a journal club by presenting academic research papers and communicating complex ideas to non-technical audiences. This position focuses on creating algorithmically driven features for the platform while ensuring code simplicity and performance across various high-scale data environments and production services.

What does a Applied Scientist earn?

Median $208800 from 47 postings across 10 companies.

See salary data

What you'll do

  • Research and benchmark relevant algorithms to find the best fit for specific product use cases.
  • Build new scalable product features using machine learning algorithms and statistical techniques.
  • Develop, deploy, and monitor new and existing features in production environments.
  • Analyze high volumes of streaming data to identify trends and tell a story behind the data.
  • Maintain and monitor the models, services, and infrastructure owned by your team.
  • Participate in an on-call rotation to ensure system reliability.
  • Present latest academic research papers to the team during journal club sessions.

What we're looking for

  • Hold a BS, MS, or PhD in Computer Science, Engineering, Machine Learning, or a related scientific field (or equivalent experience).
  • Experience working with high-scale systems and large datasets.
  • Experience building models and applying machine learning to real business problems.
  • Experience writing production data pipelines.
  • Ability to explain complex ideas and algorithms to non-technical audiences.
  • Commitment to code simplicity and performance.

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