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Lead Data Scientist
Il y a 2 mois
About Datadog
Datadog is a leading platform for monitoring and observability, empowering organizations to understand their complex systems and applications.
Your RoleAs a Staff Data Scientist, you will play a pivotal role in shaping the future of Datadog's data science capabilities. You will be responsible for identifying high-impact business opportunities, designing innovative solutions, and collaborating with cross-functional teams to bring your ideas to life.
What You'll Do- Drive Innovation: Uncover valuable insights from data through exploration, prototyping, and bootstrapping projects. Develop cutting-edge machine learning models and pipelines that address real-world business challenges.
- Build & Scale Solutions: Design, implement, and operationalize scalable machine learning systems for both batch and real-time use cases, handling structured and unstructured data.
- Collaborate & Mentor: Work closely with data scientists, engineers, and product managers to develop next-generation features. Guide and mentor junior team members, fostering a culture of excellence in data science practices.
- Communicate Impact: Present your work internally to technical, engineering, and product stakeholders, driving iteration and generating excitement for your solutions.
- Shape the Field: Engage with the broader data science and engineering community to advance Datadog's position as a leader in innovation.
You are a passionate and experienced data scientist with a proven track record of success.
- Technical Expertise: Possess deep understanding of the machine learning lifecycle, best practices, algorithms, and domains such as anomaly detection, natural language processing, computer vision, personalization, and recommendation systems.
- Collaborative Mindset: Thrive in a collaborative environment, effectively communicating with stakeholders from diverse backgrounds and leveraging domain expertise to develop impactful solutions.
- Software Engineering Skills: Demonstrate strong coding skills in languages like Scala or Python, and familiarity with software engineering principles such as testing, code reviews, and deployment.
- Data Engineering Knowledge: Have a fundamental understanding of data engineering practices, including data pipeline creation, processing, and storage using technologies like Spark.
- Product Focus: Approach problem-solving with a product-oriented mindset, considering user experience and business impact in your solutions.
- Communication Prowess: Communicate clearly and effectively to audiences of varying technical levels, both verbally and in writing.
