About the role
We're looking for an experienced Data Science & Analytics Manager to lead, grow, and develop a team of analysts and data scientists who partner directly with our business stakeholders. This is a people-first leadership role where you'll balance team development with strategic business partnership.
You'll ensure the right work gets done by the right people at the right time, translating business priorities into team capacity, developing talent across both analytics and data science disciplines, and ensuring our work drives measurable business outcomes. Critically, you'll work closely with business leaders to mature their data literacy, analytics capabilities, and self-service frameworks—coaching them on how to engage with data productively and building sustainable analytics practices.
The ideal candidate brings substantial experience managing high-performing analytics teams in fast-paced environments, has a track record of strong business partnerships, and understands how to build analytics maturity in organisations at different stages of data sophistication. You're comfortable navigating ambiguity, translating between technical and business languages, and building trust with stakeholders at all levels.
What you will be doing
Strategic Business Partnership:
Embed deeply with Go-to-Market and Internal Enablement teams (Systems, Finance, Strategy, Risk) to understand their business challenges and priorities
Translate business strategy into analytics team roadmap and priorities
Partner with business leaders to identify high-impact opportunities where analytics and data science can drive value
Build trusted advisor relationships with stakeholders at all levels, including senior leadership
Navigate organisational dynamics and competing priorities to secure resources and alignment
Represent the analytics function in leadership forums and strategic planning discussions
Analytics Maturity & Capability Building:
Assess and mature data frameworks, analytics processes, and self-service capabilities across business groups
Coach business partners on how to engage with data effectively – from asking the right questions to interpreting insights
Build data literacy across the organization through training, documentation, and hands-on support
Work with teams at different levels of analytics maturity, meeting them where they are and helping them progress
Establish standards for analytical work, documentation, and knowledge sharing
Invest in tools, infrastructure, and processes that enable the team to scale their impact
Delivery & Operational Excellence:
Prioritise across competing demands – balancing strategic projects with operational needs
Allocate resources effectively across analytics and data science initiatives
Build delivery systems and processes that drive clarity, accountability, and quality at speed
Remove blockers, manage risk, and ensure teams have what they need to succeed
Communicate progress, setbacks, and team impact clearly to stakeholders
Balance short-term delivery with long-term capability building
Strategic Planning & Execution:
Translate business objectives into analytics roadmap with clear priorities and success metrics
Make data-driven decisions about team investments, tools, and resource allocation
Anticipate future analytics needs and build capabilities proactively
Balance strategic, high-impact work with operational support and ad-hoc requests
Ensure analytics work is aligned to business outcomes and demonstrates clear ROI
People Leadership & Team Development:
Recruit, develop, and retain top analytics and data science talent with diverse skill sets
Provide clear coaching, feedback, and performance management across both analytics and data science tracks
Create growth pathways and development opportunities tailored to individual strengths and career aspirations
Foster a high-performing team where people challenge each other and grow together
Handle difficult conversations and performance issues with care and directness
About you
Essential experience:
5+ years managing analytics, data science, or business intelligence teams, with demonstrated success developing talent and delivering business impact
Proven track record as a hands-on business partner – deeply embedded with business stakeholders, influencing decisions, and translating between technical and business contexts
Experience building analytics maturity in organisations, including developing data literacy, self-service frameworks, and analytics best practices
Strong understanding of both analytics and data science disciplines – you can speak credibly about SQL, statistical methods, experimentation, and ML approaches
Track record working with business functions at different levels of data sophistication, meeting them where they are and coaching them forward
Experience managing cross-functional partnerships with go-to-market, finance, operations, or risk teams
Comfortable navigating ambiguity, managing competing priorities, and making tough decisions with incomplete information
How you work:
People first: You genuinely care about developing people and building high-performing teams. You create psychological safety while maintaining high standards
Business embedded: You don't manage from a distance – you're in the weeds understanding business problems, building relationships, and earning trust through results
Clarity and communication: You provide crystal-clear direction, adapt your message to your audience, and communicate team impact compellingly
Pragmatic and decisive: You balance trade-offs, make sound decisions with incomplete information, and know when to act vs. when to gather more data
Maturity builder: You have a nose for where analytics capabilities are immature and a toolkit for how to develop them – whether that's better tooling, training, processes, or coaching
Results oriented: You focus relentlessly on business outcomes, not just outputs. You connect analytics work to measurable impact and demonstrate ROI
Organisationally savvy: You navigate politics effectively, influence without authority, build coalitions, and get things done in complex environments
Growth mindset: You learn from mistakes, seek feedback actively, and continuously improve how you lead and how your team operates
Nice to have:
Background as a senior analyst or data scientist yourself – you've done the work and understand what your team experiences
Experience in fintech, payments, or high-growth technology companies
Familiarity with modern analytics tools and data stack (SQL, Python/R, BI platforms, workflow orchestration)
Understanding of experiment design, causal inference, or machine learning applications
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