Director of Data Science

Descrição do trabalho

Role Overview

We are seeking an experienced Director of Data Science to lead our Data Science, AI, and ML research initiatives. This role will focus on driving innovation, experimentation, and rapid prototyping of advanced analytical models and algorithms. The Director of Data Science will collaborate closely with cross-functional partners—including product, engineering, and operations—to identify opportunities, validate ideas, and provide data-driven insights that can shape the strategic direction of our products and services.

• Please note that we have a separate Machine Learning capability within Engineering which is responsible for building, training, deploying, and monitoring the models we run in production. Therefore, while the Data Science function will prototype new algorithms, validate research directions, and inform product development, the hands-on productionisation of these models will be managed by the ML Engineering team.
• Key Responsibilities
• Team Leadership
• Build, scale, and lead a world-class data science team (currently based in London and Lisbon)
• Make ComplyAdvantage a great environment for Data Scientists to operate in. Building clear career progression frameworks; ensuring appropriate tooling and technology are in place
• Data Science Strategy and Leadership
• Define and implement the strategic vision for the Data Science function, ensuring alignment with business goals and a 3–6 month innovation horizon.
• Manage, mentor, and develop a high-performing team of Data Scientists and Researchers, fostering a culture of collaboration, curiosity, and impact.
• Research and Prototyping
• Lead the design and execution of AI/ML research projects, focusing on cutting-edge techniques and their potential application in our products and services.
• Oversee rapid prototyping efforts, ensuring that the resulting proof-of-concepts can be effectively transferred to the ML Engineering team for productionisation.
• Collaboration and Stakeholder Management
• Partner with Product Managers, Engineers, and other stakeholders to identify and prioritise research projects that address critical business challenges and opportunities.
• Communicate findings, recommendations, and progress updates to senior leadership and cross-functional teams, translating complex technical concepts into actionable insights.
• Data Governance and Ethics
• Promote and uphold best practices in data integrity, privacy, and security, collaborating with compliance and legal teams where necessary.
• Champion ethical AI and ML practices within the team, ensuring all research adheres to regulatory requirements and ethical guidelines.
• Performance Measurement and ROI
• Establish relevant KPIs to measure the impact and success of data science initiatives (e.g., model accuracy, time-to-insight, incremental revenue opportunities).
• Evaluate the effectiveness of research projects post-implementation to inform continuous improvement and guide future priorities.
• Thought Leadership
• Stay current with industry trends and emerging technologies in AI/ML, data science methodologies, and tools.
• Represent the company at conferences, webinars, and industry events to showcase our data science capabilities and thought leadership.

• Qualifications
• Education:
• Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Data Science, Statistics, Mathematics, Engineering).
• PhD in a relevant field (strongly preferred) but not mandatory if combined with demonstrable industry leadership experience.
• Technical Expertise:
• Strong foundation in machine learning, AI, statistics, and data mining techniques.
• Familiarity with a range of data science and analytics tools (e.g., Python, R, SQL, Spark, TensorFlow, PyTorch).
• Experience working with large datasets, cloud-based infrastructures, and modern data platforms.
• Experience working with large language models (LLMs) and agentic AI frameworks is desirable, since both of these form a significant part of our work and of the data science roadmap
• Leadership & Management:
• Proven track record in building and leading data science teams, preferably within a fast-paced or innovative environment.
• Experience managing projects through the entire research lifecycle, from ideation to proof-of-concept.
• Business Acumen:
• Ability to understand and translate business challenges into data science problems and actionable insights.
• Strong stakeholder management and communication skills, with a demonstrated capacity to influence and present at senior leadership levels.
• Collaboration & Communication:
• Excellent written and verbal communication skills, capable of explaining complex technical topics to non-tech