Head of Data Insights,

Introduction: Since Aspen was founded in 2002, we have become a leading, diversified specialty insurance and reinsurance company. We respond thoughtfully and creatively to find the best outcomes for our clients and business partners through carefully tailored solutions. We believe the way we work is just as important as the work we do, and we are guided by our core values of respect, honesty, trust, and professionalism. Aspen is a great place to develop your career offering an exciting and challenging environment where achievement is rewarded.

The Role: Aspen’s vision is to be the global reference point for quality in all its markets. Regarding data, Aspen has a common principle to ensure that its data is accurate and fit for purpose to support business decision-making, promote trust in reporting and provide client intimacy.

The role of the Head of Data Insights is to establish a strong analytics and AI capability in support of the business needs to become a data led company.

As the Head of Data Insights, your primary responsibility is to oversee the strategic utilization of data to drive informed decision making across all departments. You will be the lead of a team of data analysts and scientists, setting the strategy and delivering actionable insights from our single version of truth Lakehouse architecture. You will co-develop our data driven strategy that will focus on effective data storytelling, translate complex analytical findings into actionable recommendations and through a comprehensive training program, empower our users to adopt insights for more informed decision making.

Key Responsibilities:

Strategy and Planning

• Set and regularly update the enterprise analytics strategy and organizational model in close association with the Group Data & Analytics Leadership team ensuring that this is embedded and understood across the organization.
• Define the agile framework and processes enabling every function to turn requirements and ideas into insights that support data based decisions.
• Adopt DevOps, DataOps and MLOps frameworks and best practices as the standard for all data engineering across the company.
• Development and monitoring of MI and AI engineering quality metrics and responsibility for directing the appropriate remediation of breaches to these standards.
• Develop and maintain controls on data quality, interoperability, and sources to effectively manage corporate risk associated with the use of data for decision making.
• Organize and chair the Analytics and AI engineering chapter’s that meets regularly with a focus on priorities, delivery standards and capabilities across the value chain to improve processing of data and enhance our ability to make use of ML/AI in decision making of our processes.
• Coordinate alignment across the business’s utilizing our single version of data truth which will power all analytics.
• Connect with the analytical Product Owners on the business side to ensure we are reusing data but also connecting insights and providing a seamless analytical environment for users to discover, access and make use of data.
• To develop and maintain strong operational and strategic relationships with key internal customers within the business.

Policy, Process and Procedures

• Oversee the analytics chapter group, continuously reviewing alignment of delivery standards for all analytical products.
• Lead the delivery of our analytics education framework across the business. Enabling users of any data maturity level to have a path for creating and using insights for more informed decision making.
• Evolve and institutionalize behaviors for the appropriate use of data within changing security requirements, privacy needs, ethical values, societal expectations, and cultural norms.

Environmental Awareness/Customer Focus

• Build and maintain strong and effective relationships with key internal (up to executive level) and external stakeholders to ensure that service delivery meets business expectations.
• Develop our analytics strategy around the foundation of insights that support better decision making across our value chain. Focus on reusability of insights, driving better risk assessment and customer experience internally and externally to Aspen.
• Maintain oversight working closely with IT relating to the design, development, and implementation of analytical tools and models, cloud-based solutions and assignments will be key responsibilities.
• Be hands-on and agile, demonstrating a “roll up your sleeves” mentality and willingness to remain proactive in communicating with direct reports and other executives.

Technical Performance

• Provide creative insights, implications, and recommendations about current and future data analytics trends and areas for improvement, focus or investment. Ensure that commercial ambition is balanced with effective and rigorous cost management.
• Ability to utilize Azure cloud technology and services to deliver analytical solutions and tools for all users powered by a single version of data truth.
• Identifies and allocates resources to deliver demand to internal stakeholders with a disciplined approach to cost acting as a role model.
• Support the Head of Data Arch and Data Engineering with the delivery of our single version of truth.
• Build into the analytical solutions the monitoring of value from their usage. Real time insights not the adoption of tools and the realized benefits over time.
• Keep abreast of industry news and trends and perform regular market research to analyze the competitive landscape to proactively address competitive threats, inform the product roadmap and anticipate market trends and evolving client needs.

Essential Skills & Experience:

• Specific professional qualifications (and broad business qualifications) at the level of degree or equivalent.
• Must offer track record of working (ideally) in the Insurance or Financial Services Industry
• Advanced experience in coding with SQL, Python and/or R
• Offer strong knowledge of AI, GenAI, NLP.
• Offer strong knowledge of Machine Learning and Deep Learning
• Offer good knowledge of ML Ops (Docker, Kubernetes, CI/CD.

Qualified within own personal discipline, with extensive post-qualification work experience to include:

• Working with large third-party vendors/ external suppliers.
• Managing relationships with internal business customers at a senior level.
• Strong track record of technology delivery.
• Managing cross functional teams and matrix management.
• Interpreting business strategy and translating this into IT strategy.
• Project management/co-ordination, including managing multiple projects and complex projects to quality, time, and budget.

In addition:

• Offer an entrepreneurial and creative approach to developing new, innovative ideas that will stretch the organization and push the boundaries.
• Bring immense curiosity; challenging the status quo and stirring innovative approaches to existing processes and operations.
• Excellent organizational, leadership and people-management skills.
• Technical acumen – ability to understand how technology and data can support the business.
• Finance management - including budget management, forecasting and cost analysis.
• Resource and budget management (across functional teams)
• Strong interpersonal and communication skills.
• Problem solving and decision-making skills.
• Strong customer orientation skills.
• Able to manage conflicting priorities to achieve deadlines.
• Able to plan effectively and efficiently.
• Ability to collaborate effectively within a team.
• Proficient in MS Office applications.

At Aspen we know that having a diverse and inclusive workforce is good for our people, good for our business and good for the environments in which we operate. We therefore welcome applications from people which allows us to draw on diverse cultures, perspectives, skills, and experiences.

Candidates must be elidable to work in the UK full time