Staff Data Scientist
| Company | Fastly |
|---|---|
| Location | San Francisco, CA, USA, New York, NY, USA, Denver, CO, USA |
| Salary | $181220 – $217464 |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Senior |
Requirements
- Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field
- 5+ years of professional experience applying data science and AI techniques to solve business problems, with demonstrated expertise solving complex and highly impactful quantitative business problems
- Strong programming skills in Python and experience with data science and AI libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face)
- Expertise in statistical analysis, machine learning algorithms, experimentation methodologies, large language models, and generative AI frameworks
- Experience mentoring and leading others in data science skills and initiatives
- Experience working with modern data stacks, including Airflow, Fivetran, dbt, BigQuery, Vertex AI, and Looker
Responsibilities
- Lead end-to-end data science and AI projects from problem definition and data collection to model deployment and business implementation
- Design, develop, and optimize machine learning and generative AI models to solve complex business problems and drive measurable outcomes
- Integrate AI capabilities into existing products and workflows to enhance functionality and create new value opportunities
- Collaborate with engineering, product, and business teams to identify opportunities where data science and advanced AI can create significant impact
- Communicate insights and recommendations to technical and non-technical stakeholders through compelling visualizations and presentations
- Mentor junior team members and establish best practices for the team’s AI approaches and methodologies
Preferred Qualifications
- Domain expertise in our industry or related fields
- Experience deploying and maintaining production machine learning systems
- Experience with specialized data types such as natural language, time-series, or recommendation systems
- Track record of leading technical teams or mentoring junior data scientists
- Implementing and fine-tuning large language models or other generative AI systems for specific business applications
- Building AI-powered products or features that have been successfully deployed to end users
- Experience with prompt engineering and RAG systems
- Contributions to open-source AI projects or research publications in machine learning or generative AI
- Proficiency with AI services on cloud platforms (AWS Bedrock, GCP Vertex AI, Azure OpenAI)