Fastly is looking to solve critical business challenges by delivering actionable deep insights through data-driven decision-making, and to create a more trustworthy Internet.
Requirements
- Significant professional experience in a related technical or ecommerce field, applying data science and AI techniques to solve diverse business problems
- Strong programming skills in SQL and 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 working with modern data stacks, including Airflow, Fivetran, dbt, BigQuery, Vertex AI, and Looker
- Experience mentoring and leading others in data science skills and initiatives
- Experience deploying and maintaining production machine learning systems
- Experience with specialized data types such as natural language, time-series, or recommendation systems
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
Other
- Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field
- Related CDN industry experience
- Experience in small to mid-size organizations where you have hands on experience and decision making input on building and expanding the data ecosystem
- Ability to work during core business hours and participate in an on-call rotation
- Availability to work in a hybrid model with flexibility to split time between office and home
