---
title: 'Senior Applied Scientist - Behavior AI at Datadog'
canonical: 'https://feeny.ai/job/senior-applied-scientist-behavior-ai-datadog-paris-rjbqv25d5xsk'
type: 'job'
last_seen: '2026-10-17'
---

# Senior Applied Scientist - Behavior AI at Datadog

- **Company:** Datadog
- **Location:** Paris, France
- **Posted:** 2026-07-06
- **Last confirmed live:** 2026-10-17
- **Apply:** https://careers.datadoghq.com/detail/8045964/?gh_jid=8045964

## Job description

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record.

We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all.

The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you.

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:

- Design and build custom mid-size models for high-throughput stream processing, and train them at scale.
- Optimize these models from start to finish, working across both the mathematics and the systems, often by finding mathematical reformulations that fit the hardware and software constraints better.
- Build the training data pipelines the work depends on when they do not already exist, from the raw stream to a training-ready dataset.
- Work with engineering to integrate models into production, with a clear focus on GPU utilization, latency, and cost per record on live traffic.
- Plan the roadmap of model and system improvements, based on a solid understanding of the product and of what matters most to users.
- Build an agentic layer on top of the models to analyze, validate, and act on their outputs.
- Build lightweight interpretability tools that make model behavior easier to explain to the people who rely on it.
- Maintain and monitor the models, services, and infrastructure your team owns, and take part in your team's on-call rotation.

Who You Are:

- You have a BS/MS/PhD in Computer Science, Engineering, Machine Learning, Applied Mathematics, or a related scientific field, or equivalent experience.
- You have hands-on experience training and fine-tuning models at scale, and deploying them into production systems with real throughput and cost constraints.
- You have a working knowledge of how GPUs work, and a track record of making models run efficiently within real hardware constraints.
- You have strong applied-mathematics fundamentals and reach for them naturally when designing and optimizing models.
- You have a real passion for applied mathematics, software design, and implementation. This role sits at the intersection of the three, and it is a requirement for the position.
- You care about code simplicity and performance, and you can build the data pipelines and the surrounding production code, in addition to the models themselves.
- You can explain complex ideas and trade-offs clearly to engineers and product partners, and you let a solid understanding of the product guide what you build next.
- Bonus: experience with efficient sequence architectures, model interpretability, or large-scale streaming systems.

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
- Opportunity to attend and present at conferences and meetups, and to publish your work
- Intra-departmental mentor and buddy program for in-house networking
- An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
- Competitive global benefits

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

About Datadog, Equal Opportunity, and Privacy and AI Guidelines boilerplate is appended automatically by the applicant tracking system. Add Datadog's current standard blocks before publishing.

#LI-Hybrid

About Datadog:

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on [Instagram](https://www.instagram.com/datadoghq/?hl=en), [LinkedIn,](https://www.linkedin.com/company/datadog) and [Datadog Learning Center.](https://learn.datadoghq.com/)

Equal Opportunity at Datadog:

Datadog is proud to offer [equal employment opportunity](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our [Candidate Legal Notices](https://www.datadoghq.com/legal/candidate-legal-notices/) for your reference.

Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete [this form](https://docs.google.com/forms/d/e/1FAIpQLSeoJeduEZ2NdZF_65uZmWUrCM-zee7yADXX1s6Xr9zAGq8iKA/viewform). This form is for accommodation requests only and cannot be used to inquire about the status of applications.

Privacy and AI Guidelines:

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s [Applicant and Candidate Privacy Notice](https://www.datadoghq.com/legal/applicant-candidate-privacy/). For information on our AI policy, please visit [Interviewing at Datadog AI Guidelines](https://www.datadoghq.com/legal/interviewing-at-datadog-ai-guidelines/).

## About Datadog

## Company Overview
- **One-liner**: Datadog provides a unified cloud monitoring and security platform for developers, IT operations, and business teams to gain end-to-end visibility across their entire technology stack.
- **Entity Type**: Public (NASDAQ: DDOG)
- **Headquarters**: New York, NY, United States
- **Founded**: 2010
- **Founders**: Olivier Pomel and Alexis Lê-Quôc

## Core Business
- **Primary industries**: Cloud monitoring, observability, application security, IT operations, DevOps
- **Target customers**: B2B – from SMBs to large enterprises, serving developers, IT operations, security teams, and business users
- **Mission/purpose**: “We are building the modern monitoring and security platform for developers, IT operations teams and business users in the cloud age.” [datadoghq.com](https://www.datadoghq.com/)

## Products & Services
- **Infrastructure Monitoring**: Metrics collection and visualization for servers, containers, cloud services, and hybrid environments.
- **APM (Application Performance Monitoring)**: Trace and optimize application performance end-to-end.
- **Log Management**: Centralized log ingestion, analysis, and exploration with sensitive data scanning and audit trail.
- **Security**: Unified security and observability – including Cloud SIEM, Application Security Management, and runtime detection to defend against AI-powered attacks. [datadoghq.com](https://www.datadoghq.com/product/security/)
- **Digital Experience Monitoring (DEM)**: Synthetic monitoring (browser & API tests) and Real User Monitoring (RUM) for frontend performance.
- **Bits AI**: AI agents that chat, investigate, and remediate issues; includes Watchdog for proactive anomaly detection.
- **Network Monitoring**: Analyze network traffic patterns across cloud environments.
- **Service Management** and **Software Delivery**: Incident response, workflow automation, CI Visibility, DORA Metrics, and OpenTelemetry support.
- **Database Monitoring** and **Data Streams Monitoring**: Deep visibility into databases and streaming pipelines.

## Market Standing
- **Valuation/Market Cap**: ~$39.9 billion (as of mid-2026) [linkedin.com](https://www.linkedin.com/company/datadog)
- **Key Metric**: FY2025 annual revenue of $3.43 billion [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-datadog-2026)
- **Notable Investors/Partners**: Index Ventures (led Series C), with total funding of ~$1.67 billion including IPO proceeds. [linkedin.com](https://www.linkedin.com/company/datadog)
- **Growth Signals**:
  - Recognized as a Leader in the **Gartner Magic Quadrant for Observability Platforms** and for **Digital Experience Monitoring**; also named a Leader in **The Forrester Wave: AIOps Platforms, Q2 2025**. [datadoghq.com](https://www.datadoghq.com/)
  - Headcount grew to approximately **10,100 employees** by April 2026 (up from ~8,100+ reported earlier). [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-datadog-2026)
  - Maintains a strong Glassdoor rating of **4.2/5.0**, with ~80% of employees recommending to a friend. [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-datadog-2026)

## Competitive Advantages
- **Unified platform**: Combines infrastructure monitoring, APM, log management, and security in a single solution – reducing tool sprawl.
- **AI-native capabilities**: Bits AI agents and Watchdog provide automated root-cause analysis, remediation, and proactive insights.
- **Industry recognition**: Consistently placed as a Leader in multiple analyst quadrants (Gartner, Forrester), validating product quality and market presence.
- **Scale and ecosystem**: 700+ integrations, a rich marketplace, and broad support for OpenTelemetry and other open standards.

## Strategic Focus
- **AI and automation**: Deep investment in AI-driven features (Bits AI, Watchdog, automated remediation) to reduce toil and improve mean-time-to-resolution.
- **Security observability**: Extending the platform to unify security and observability – a key differentiator as threats become more complex.
- **Global expansion**: Growing employee presence across the Americas, EMEA, and Asia Pacific (53 countries) to serve a widening customer base. [careers.datadoghq.com](https://careers.datadoghq.com/)

## Why Work Here
- **Culture**: Transparent, inclusive, and engineering-driven. Diversity and inclusion are core values, with active Employee Resource Groups. [careers.datadoghq.com](https://careers.datadoghq.com/)
- **Flexibility**: Operates a flexible work environment supporting remote, hybrid, and office cultures – “Innovation happens everywhere”. [careers.datadoghq.com](https://careers.datadoghq.com/)
- **Benefits**: Generous benefits tailored by region, covering physical, mental, and financial wellness. [careers.datadoghq.com](https://careers.datadoghq.com/)
- **Growth**: 454 open positions globally (as of mid-2026) across engineering, sales, product, marketing, and technical solutions – with opportunities to work on cutting-edge observability and AI challenges. [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-datadog-2026)
- **Ratings**: CEO Olivier Pomel enjoys ~87% approval; overall Glassdoor rating is 4.2/5.0 (Work-Life 3.8, Compensation 3.9, Culture 4.0). [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-datadog-2026)

## Sources
1. [datadoghq.com](https://www.datadoghq.com/)
2. [careers.datadoghq.com](https://careers.datadoghq.com/)
3. [jobsbyculture.com](https://jobsbyculture.com/blog/working-at-datadog-2026)
4. [linkedin.com](https://www.linkedin.com/company/datadog)

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