Senior Director, Data Science at 2U

Summary of Job:

• The Sr. Director, Data Science will lead a global team responsible for harnessing the power of data science to drive strategic initiatives across the organization.  This role is critical in aligning the data science function with business objectives, ensuring optimal use of machine learning/artificial intelligence (ML/AI), experimentation, and other advanced analytics to address key business problems. This position requires deep technical expertise, strategic vision, and proven leadership skills to manage and grow a high-performing global team. The Snr Dir, Data Science will be responsible for building, scaling, productionizing, and optimizing data science initiatives that impact core business functions like marketing, product development, and operations. This is a highly quantitative role that requires elite analytical aptitude, strong programming and engineering skills, strong interpersonal and management skills, and intellectual curiosity. We are looking for someone who has a history of using data science to solve business problems, has extensive experience training and evaluating machine learning models in production, and a proven ability to manage people and grow teams.

Key Role and Responsibilities: 

• Strategic Vision & Business Alignment 
• Work closely with stakeholders across departments, as well as external stakeholders such as Red Ventures, to integrate data science solutions into business processes and identify opportunities for optimization through AI/ML, experimentation, and advanced analytical products. . 
• Maintain direction. Ensure team is aligned at all times on changes associated with business priorities in order to meet performance expectations through tools like product roadmaps, OKRs, etc..
• Alignment. Assisting and influencing business stakeholders at all levels in defining data science projects/products  based on business priorities. Ability to take business direction, work through ambiguity and drive execution balancing shorter term planning and prioritization with long term vision. 
• Stakeholder Partnership Balance the team’s focus on known business problems and existing solutions with taking risks into new/novel areas, focusing on revenue optimization or cost reduction.  
• Team Leadership and Development 
• Support, mentor, guide direct and indirect reports.
• Continuously manage performance and professional development  of direct reports through regular 1:1s, ad-hoc feedback, bi-annual performance reviews. 
• Cultivate an inclusive,  engaging, and well-defined work environment to retain and attract top talent, growing the team per business needs. 
• Mentor and coach managers in the team to establish their own leadership style, aligning to 2U’s competency guides.
• Define and implement business processes, procedures and policies for the data science team, where applicable.
• Recognise high performance and reward accomplishments.
• Define and implement strategies to strengthen team engagement and morale.
• Identify retention strategies with talent team.
• Identify and manage future growth of team as per business needs.

System and Product Ownership

• Oversee the design, development, and deployment of machine learning models and decision engines that address complex business problems.
• Lead efforts to implement best practices in model training, validation, and performance evaluation across diverse datasets.
• Collaborate with outside engineering teams to productionize machine learning code, automate workflows, and integrate models into the broader 2U technical ecosystem.
• Ensure the integrity and accuracy of data science products while driving continuous improvements in efficiency, cost, and long-term impact.
• Operational Excellence & Innovation 
• Drive the efficient execution of data science initiatives, ensuring alignment with agreed-upon timelines and resourcing plans.
• Oversee the development of technical processes, including model development, testing, code review, job workflow optimization, and job scheduling.
• Manage the data science team’s budget, collaborating with global teams to identify cost-saving opportunities and optimize resources.

Personal Development

• Strategic thinking skills
• Postgraduate studies in management/related
• Skills to be developed for career progression

Education and Experience:

• 10+ years’ experience in working in applying machine learning and advanced analytical techniques in a fast-paced business environment.  Experience in marketing and sales optimization is a plus. 
• 3+ years in a leadership role in the Data field, with experience managing global, high-performing teams. 
• Proven track record in deploying machine learning models in production environments, with experience in Python and/or R, and SQL.  Foundation in working in distributed cloud environments and container technologies (i.e. Docker, Kubernetes) to manage workflows.  
• Excellent communication skills, with the ability to simplify complex data and technology concepts to stakeholders at all levels. 
• Minimum Engineering / Informations Systems / Computer Science / Econometrics degree or related.