Job Description

You, as our Director of Data Products and Data Science, will be overseeing our Data Products Management, Data Science and Machine Learning Engineering teams ensuring a data driven approach is at the heart of what we do. You’ll work across the business, not only ensuring your teams provide timely actions, but also spending considerable time looking for those ‘unknown unknowns’ that really provide a WOW! moment for the business.

If you believe that through your strategy and direction, you can build a hive-mind people structure across multiple locations, focused on complex analytical requirements that shape our business planning and delivery, this role could be right up your street. You most likely feel that BI should be delivered in a certain way, for instance, you’ll expect your analysts, managers, senior managers and department heads to always be thinking within the framework of an analyst’s mind, namely:

Do they really need to understand why? Why do things work the way they do? Why don’t we try something different? Why some people play Game A in preference to Game B. Why do some people react more positively to player promotions than others?

You will be required to;

• Partner with Business, Product, Engineering, and cross-functional teams to inform, influence, support, and execute customer centric product strategy
• Inspire, lead and grow a globally distributed team of data scientists and ML engineers
• Develop in depth business understanding and championing Data Science domain as a key enabler in achieving company goals, resulting in concrete roadmap deliverables
• Evolve operating model across ideation, proof of value and scale up to fully realize value from the data products
• Own Data products roadmap and it’s continuous delivery pipeline, successfully drive value through automation in scale and improvement of customer experience. Communicate the achievements
• Develop and implement a fully modular approach to data product development to allow the team to increase capacity by “develop once deploy anywhere”, designing robust processes around ML deployment practices
• You will bring an innovation agenda, technical thought leadership capability and vision for the next evolution of AI/ML data products at Flutter International
• Maintain an effective long-term relationship with technology and engineering teams
• Work with Senior Director of Data and Analytics to influence the data strategy across the organization

What’s in it for you?

Our experience-based salaries are competitive. Plus, there’s a discretionary annual performance bonus. And we provide advice and dedicated assistance to those moving to Leeds.

• Health and dental insurance for you, your partner and your children (if you all live at the same address)
• The option to join our company pension scheme
• £1,000 as a congratulations if you have a baby whilst you work for us
• Discounted gym membership
• In-house training and development to develop your skills, progressing your career
• Free fresh fruit, snacks and drinks in the office
• Social events; including our sensational summer and christmas parties.

Required Knowledge, Skills, and Abilities

Degree in an applied quantitative field (Statistics, Mathematics, Economics, Engineering or CS). Extensive experience in machine learning, mathematical, statistical or other quantitative skills and demonstrate sound knowledge in a breadth of ML techniques. Proven experience managing analytics teams, working collaboratively with Product, Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development. Proven experience influencing product strategy and drive change across organizational boundaries through clear and compelling communication of data-driven insights and analyses. Able to communicate complex data science models visually and simply to senior non-technical audiences. Apply appropriate frameworks to assess and priorities workload. Ability to coach and mentor team members. Leveraging multiple cloud-based and open source ML / AI frameworks. Strong evidence of deploying data products into production and quantifiable business value delivered. Highly organized.