Staff Data Scientist

Company: Optimizely

At Optimizely, we're on a mission to help people unlock their digital potential by reinventing how marketing and product teams work to create and optimize digital experiences across all channels. With Optimizely One, our industry-first operating system for marketers, we offer teams flexibility and choice to build their stack their way with our fully SaaS, fully decoupled, and highly composable solution. We are proud to help more than 10,000 businesses, including H&M, PayPal, Zoom, and Toyota, enrich their customer lifetime value, increase revenue and grow their brands. Our innovation and excellence have earned us numerous recognitions as a leader by industry analysts such as Gartner, Forrester, and IDC, reinforcing our role as a trailblazer in MarTech.

Our culture is dynamic and constantly evolving, shaped by every employee, their actions and their stories. With over 1500 Optimizers spread across 12 global locations, our diverse team embodies the "One Optimizely" spirit, emphasizing collaboration and continuous improvement, while fostering a culture where every voice is heard and valued.

Staff Data Scientist Opportunity

We are seeking an exceptional Staff Data Scientist who will architect and technically lead projects dedicated to pushing the boundaries of AI-driven digital experiences. In this pivotal role, you will guide the development of cutting-edge machine learning solutions that not only anticipate but actively shape how global brands engage, understand, and delight their customers through intelligent, predictive, and personalized digital interactions.

Why is this team critical to Optimizely?

• Business Impact: Powering Optimizely One, our ML innovations are crucial for defining Optimizely's technological leadership in digital experience platforms.

• High Visibility: ML capabilities developed by this team are central to Optimizely's strategic product roadmap and cross-product integration.

• Shape the Future: We are positioned to define the next generation of intelligent digital interaction across global brands.

Some technologies we work with:

• Python primarily, with bits and pieces of Typescript and Scala
• GCP, AWS, Azure – in this order of relevance
• GitHub, Docker, GitHub Actions, Terraform, Kubernetes
• Pandas, PySpark and Spark
• Vertex AI, Azure OpenAI for LLMs

Job Responsibilities

• Lead the execution of projects in a high-performing data science team, fostering professional growth and creating an inclusive and collaborative environment
• Architect and design scalable machine learning systems that solve complex challenges
• Develop and execute the data science team's strategic roadmap, managing complex projects from conception to deployment
• Make high-impact technical decisions and provide guidance
• Establish best practices in software engineering and machine learning development
• Implement rigorous code quality and testing standards across data science projects
• Support talent acquisition and continuous learning initiatives

Knowledge and Experience

• 7+ years of experience in data science, with at least 3 years in a technical leadership role
• Strong technical mentorship and team development capabilities
• Proven track record of designing and implementing production machine learning solutions
• Strong technical background with demonstrated ability to lead complex ML initiatives
• Excellent programming skills in Python and experience with machine learning frameworks
• Deep understanding of Machine Learning algorithms, Recommender Systems, Natural Language Processing, Generative AI and Large Language Models
• Experience with at least one cloud platform (GCP, AWS, Azure)
• Strong in version control (GitHub) and experience with CI/CD tools (GitHub Actions)
• Demonstrated expertise in test-driven development and clean code principles
• Proven ability to write maintainable, modular, and well-documented code
• Exceptional English communication skills

What sets you apart:

• Proficiency in distributed data processing (Spark, cloud services)
• Knowledge of ML model development and deployment frameworks (MLFlow, Kubeflow)
• Advanced data querying (SQL) and data engineering pipelines (Airflow)
• Extensive experience with comprehensive unit testing, integration testing, and test coverage strategies
• Experience working with Product Management teams and ability to translate complex technical concepts for non-technical stakeholders