Senior Data Scientist

  • Optimizely
  • Remote (London SE1, UK)
  • 10/02/2024
Full time Data Science Big Data Statistics Biostatistics Data Warehouse

Job Description

Optimizely is known for content, commerce, and optimization with our Digital Experience Platform (DXP). Millions of experiences are served with our platform every single day, helping organizations grow exponentially online. We have the honor of serving some incredible customers – which makes what we do extremely rewarding. Optimizely has over 9,000 brands, from global organizations such as Visa, Sky, Yamaha, and Wall Street Journal to tech innovators like Atlassian, DocuSign, FitBit, and Zillow.

Not only are we financially sound and growing, but we have unicorn status: we exceeded $300M in revenue in 2020, is profitable already, and have all strategic options ahead of us. Optimizely continues to invest and addresses a market opportunity north of $30 billion, providing significant personal career growth opportunities.

We are an inclusive culture with a global team of 1200+ people across the US, Europe, Australia, Bangladesh, UAE, Singapore, and Vietnam. We blend European and American business cultures, emphasizing teamwork, inclusion, and moving fast. People make the difference!


Our Data Science team harnesses big data, natural language processing, and machine learning to help create next generation products for Optimizely’s Experimentation, CMS, e-commerce, and data platforms.

This team emerged as a result of the acquisition of two start-ups (Peerius and Idio) that provided personalisation products for e-commerce and content. Over the past years, the consolidated company has improved the lives of customers such as Intel, HP, Fitch Ratings, Sainsbury’s and many other brands. Episerver’s acquisition of Optimizely has paved the way for interactions between data-driven experimentation and AI.

This role is within a team whose primary focus lies in the following areas: Natural Language Processing, Machine Learning, and Recommendation Systems. Our stack employs a variety of technologies, including (i) code written in Python, Scala, and TypeScript, (ii) data pipelines using Spark, Luigi, Kubernetes, and Terraform, (iii) prototyping and deploying Machine Learning solutions using Pandas, Scikit-learn, and Dask.

Job Responsibilities

As a Senior Machine Learning Engineer, you will play a pivotal role in developing and implementing advanced ML systems that drive our company's success. In this role, you will independently develop and ship medium to large features, design and implement reliable and scalable machine learning solutions, and collaborate with the Data Science team on projects related to NLP, Recommender Systems, and Predictive modeling.

  • Develop and ship medium to large features independently or with minimal support from other team members
  • Architect, design, and implement reliable, scalable machine learning systems
  • Assist the Data Science team in maintaining and extending projects related to NLP, Recommender Systems, and Predictive modelling
  • Prototype and implement production-ready approaches based on recent research
  • Provide technical mentorship to engineers and demonstrate strong expertise in your field
  • Drive the delivery of high-quality epics in a timely manner, ensuring operational excellence in your services/components
  • Proactively communicate technical decisions, work through conflicts, and partner with Technical Leads on vision and strategy
  • Break down and solve complex problems, make explicit design trade-offs, and perform complex debugging and root cause analysis
  • Actively participate in technical discussions and team meetings
  • Effectively collaborate with cross-disciplinary team members and stakeholders
  • Deliver timely feedback to peers and manager, create an inclusive environment, and play an influential role in hiring, retaining, and growing diversity in the company
  • Apply software engineering and machine learning engineering best practices

Knowledge and Experience

  • 3+ years of hands-on experience in a development team
  • Excellent Python programming skills and experience in software development
  • Strong understanding of Machine Learning, Recommender Systems, and Natural Language Processing
  • Experience designing and shipping ML models to production environments
  • Experience with cloud computing infrastructure (AWS/Azure/GCP)
  • Experience with distributed data processing (Spark or similar cloud services)
  • Experience with data querying
  • Basic understanding of Generative AI and LLMs
  • Experience with source control tools (GitHub/GitLab)
  • Great ability to convey complex concepts to a non-technical audience
  • Understanding of the ML development life cycle and/or prior experience working with teams of ML Engineers
  • Ability to work in an inclusive environment and share our values
  • Continuous learning and improvement mindset

Bonus points:

  • Experience prototyping ideas discussed in research papers into code that can be assessed and benchmarked
  • Experience with Deep Learning / Reinforcement Learning / Statistics applied to Machine Learning
  • Experience with A/B testing
  • Experience with data processing pipeline frameworks (e.g., Luigi or Airflow)
  • Experience working with teams of Data Engineers or Product Managers
  • Experience with functional programming concepts and architecture

Keywords: Machine Learning, Data Science, GenAI, Cloud, Python, Recommendation systems, NLP, Scikit-learn, Pandas, Luigi, Airflow, Docker, Git


Bachelor's or Master's degree in Computer Science, Information Systems, or equivalent


Communicating Effectively
Critical Thinking
Managing Meetings
Prioritizing and Organizing Work
Solving Complex Problems

Our culture is the most important thing we offer. We continuously aim to provide a high-growth space, both virtually and in person, where you can do your best work and, in the process, unlock your boundless potential. We are dedicated to providing meaningful rewards and development opportunities for our employees, recognizing performance and creating a supportive working environment.