Senior Data Scientist - AI Systems for Business Teams

We build ML-powered systems that help Datadog’s customer-facing teams increase revenue and make smarter decisions. Partners include, but are not limited to, Sales, GTM Strategy and Ops, Customer Onboarding for trial-to-paid conversion, Customer Success, Marketing, and Product Management. Our work turns models into durable products that integrate with the tools these teams use every day.

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, build, and productionize machine learning systems for revenue-focused use cases such as lead and account scoring, customer onboarding conversion patterns, win/loss signal mining, feature adoption clustering, and recommendations.
• Own projects end to end: problem framing, data sourcing, feature engineering, experimentation, offline and online evaluation, deployment, monitoring, and iteration.
• Define and uphold production-readiness standards: versioned training data, reproducible pipelines, evaluation gates, model and data quality checks, rollback plans, and SLAs.
• Instrument and monitor models in production: drift detection, retraining triggers, performance dashboards, alerting, and post-launch reviews.
• Integrate model outputs into business workflows and systems such as Salesforce, Marketo, Customer Success tooling, customer onboarding systems, product analytics surfaces, and team portals.
• Partner with data engineering and platform teams to use scalable infrastructure for training, serving, scheduling, lineage, and access control.
• Contribute to shared libraries, patterns, and documentation that raise the bar for ML delivery across the org.

Who You Are:

• 6+ years of hands-on experience in applied machine learning or data science, including ownership of production ML systems.
• Strong Python skills and familiarity with common ML and data tooling; experience with platforms such as Airflow, dbt, Snowflake, Spark, or similar.
• Architected and shipped reliable models/services with CI/CD and automated tests; data/feature versioning; canary/shadow releases and safe rollbacks; clear SLOs; monitoring and alerting for drift, latency, and accuracy; retraining pipelines; incident runbooks and on-call practices; and compliance/governance best practices.
• Depth across the ML lifecycle: dataset design, disciplined experimentation, offline and online evaluation, A/B testing, observability, and safe rollout practices.
• Experience integrating model outputs into business systems and measuring impact with business KPIs.
• Comfortable working with both technical and non-technical partners; able to turn ambiguous problems into scoped, testable solutions.
• A product mindset focused on reliability, usability, and measurable outcomes.
  Bonus: experience writing back to systems like Salesforce or Marketo, or supporting Sales, Customer Success, or customer onboarding conversion workflows.

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
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• 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.