Staff Data Scientist — ML Architect & Team Leader

Optimizely AB; Stockholms kommun; On-site; SEK 900,000 - 1,200,000; Full time

Job summary

Optimizely AB is seeking a Staff Data Scientist to architect, design, and deploy scalable ML systems and to mentor team members. You will lead technical decisions, manage complex projects, and collaborate across functions to deliver large-scale initiatives.

The role requires deep ML expertise, familiarity with recommender systems and NLP, cloud infrastructure, and a strong track record in software development. You will drive best practices and contribute to a diverse, inclusive culture.

Qualifications

• 5+ years hands-on experience in a development team.
• Previous technical leadership experience in a similar environment.
• Excellent Python programming skills and experience in software development.
• Strong understanding of Machine Learning, Recommender Systems and Natural Language Processing.
• Strong experience planning, designing, and implementing scalable machine learning systems.
• 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 in conveying 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.
• 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.

Responsibilities

• Architect, design, and implement robust and scalable machine learning systems.
• Develop and ship medium to large features independently.
• Support and mentor team members by setting direction and providing guidance and feedback.
• Cultivate an inclusive environment, lead meetings effectively, and actively listen to develop empathy.
• Engage in high-leverage activities to deliver projects that solve complex problems with increased quality and efficiency in a timely manner.
• Be an expert in the relevant areas, lead technical decisions, and own related services and components.
• Gain alignment for improvements/redesigns, address conflict maturely, and effectively influence stakeholders.
• Work on complex issues, exercise independent judgment, manage project uncertainties, and make tactical decisions.
• Collaborate with cross-functional team members to develop and deploy large-scale projects.
• Advocate software engineering and machine learning best practices.
• Prioritize and balance time and resources, develop iteratively, and address cross-functional problems.
• Maintain composure under difficult circumstances, adapt to shifting priorities, demonstrate self-awareness, and deliver timely feedback to peers and manager.
• Play a key role in hiring, retaining, and growing diversity in the company.

Skills

Python

Machine Learning

Recommender Systems

Natural Language Processing

Cloud Computing

Distributed Data Processing

GitHub

GitLab

Airflow

Tools

Spark

Luigi

Job description

Optimizely AB is seeking a Staff Data Scientist to architect, design, and deploy scalable ML systems and to mentor team members. You will lead technical decisions, manage complex projects, and collaborate across functions to deliver large-scale initiatives.

The role requires deep ML expertise, familiarity with recommender systems and NLP, cloud infrastructure, and a strong track record in software development. You will drive best practices and contribute to a diverse, inclusive culture.