Simplify Logo

Full-Time

Staff Data Scientist

Data Science

Confirmed live in the last 24 hours

Datadog

Datadog

5,001-10,000 employees

Cloud monitoring and analytics solutions provider

Data & Analytics
Enterprise Software

Compensation Overview

$234k - $300kAnnually

+ Equity + Variable Compensation

Senior, Expert

New York, NY, USA

Hybrid workplace; requires some in-office presence.

Category
Data Science
Data & Analytics
Required Skills
Python
Data Science
Data Structures & Algorithms
Apache Spark
Requirements
  • 8+ years of industry experience (data scientist, ML engineer, tech lead…) and a Master’s degree or PhD in relevant fields
  • Strong track records of designing, prototyping, scaling and launching data science products to solve business problems.
  • Deep understanding of Machine Learning lifecycle, best practices, algorithms and domains (eg. anomaly detection, natural language processing, computer vision, personalization and recommendation)
  • Experience collaborating with and understanding the needs of stakeholders from a variety of business functions and ability to work with domain experts to leverage their expertise into your solution
  • Strong coding skills in general purpose languages like Scala or Python, and familiarity with software engineering principles around testing, code reviews and deployment.
  • Fundamental understandings of the data engineering practice around creation of data pipelines, processing data and storing data using technologies such as spark
  • Ability to take a product-oriented mindset in using conceptual and innovative thinking to develop and apply solutions taking into consideration the user experience
  • Proven ability to communicate clearly and effectively to audiences of varying technical levels.
Responsibilities
  • Identify high impact business opportunities through data exploration, model prototypes and bootstrapping projects.
  • Hands-on development, productionisation, and operation of machine learning models and pipelines at scale, including both batch and real-time use cases, structured and unstructured data
  • Collaborate closely with data scientists and engineers to develop the next generation of Datadog’s features
  • Mentor and guide data scientists in the organization by promoting best practices, strong technical decisions, coding standards and thorough documentation
  • Regularly present work internally (data science demo, internal talks,...) to technical, engineering and product stakeholders to iterate and generate excitement
  • Engage with the data science and engineering community to advance Datadog’s standing.

Datadog provides tools for monitoring and managing IT infrastructure in the cloud. Their services help organizations track various aspects of their operations, including application performance, security, and network health. Datadog's products work by collecting data from different sources within an organization's IT environment, allowing users to visualize and analyze this information in real-time. This helps businesses ensure their systems are running smoothly and efficiently. What sets Datadog apart from its competitors is its wide range of features that cater to different needs, such as cloud migration, DevOps practices, and IoT monitoring, all within a single platform. The company's goal is to support organizations in maintaining optimal performance and security of their IT infrastructure, regardless of their size or industry.

Company Stage

IPO

Total Funding

$147.9M

Headquarters

New York City, New York

Founded

2010

Growth & Insights
Headcount

6 month growth

17%

1 year growth

24%

2 year growth

52%
Simplify Jobs

Simplify's Take

What believers are saying

  • Datadog's strategic partnerships, such as with JFrog, enhance its platform capabilities and expand its market reach.
  • The launch of new tools like Log Workspaces and Data Jobs Monitoring highlights Datadog's focus on improving user experience and operational efficiency.
  • Significant investments from entities like Riverview Trust Co and participation in funding rounds for AI startups indicate strong financial backing and growth potential.

What critics are saying

  • The competitive landscape in cloud monitoring and analytics is intense, with major players like AWS and Google Cloud posing significant threats.
  • Frequent introduction of new features may lead to complexity and potential integration issues for existing users.

What makes Datadog unique

  • Datadog's comprehensive suite of monitoring tools, including APM, security monitoring, and IoT monitoring, sets it apart from competitors who may offer more limited solutions.
  • Their scalable subscription-based pricing model allows them to cater to both small businesses and large enterprises, providing flexibility that many competitors lack.
  • The recent introduction of features like Live Debugger and Kubernetes Autoscaling demonstrates Datadog's commitment to continuous innovation and addressing real-time operational challenges.