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Über diese Head of Analytics Stelle bei Union Maritime

Union Maritime · Vor Ort · London, England, United Kingdom

The Head of Analytics leads the group’s analysis, data and digital capability. The role leads modelling, transaction analysis and market data for Union Maritime, alongside the digitalisation and automation agenda. It uses data, analytics, automation and AI to improve the speed, quality and consistency of decision-making, and owns the models, tools and data foundations that the business relies on.

The new Head should bring strong technical and digital depth: hands-on credibility in data, financial modelling, BI, automation and applied AI, and the leadership to modernise how the group works with data.

Requirements

Transaction analysis and modelling

·         Lead the analytical evaluation of vessel acquisitions and disposals, newbuilding investments, fleet renewal and optimisation, and other strategic transactions across the group.

·         Build, own and modernise the group’s analytical and financial models, applying consistent standards, assumptions and version control.

·         Provide the analysis and models that underpin deals and transactions, including scenario and sensitivity analysis across varying market conditions.

·         Set modelling standards, templates and review processes so that transaction analysis is robust, consistent and auditable.

·         Present analysis and recommendations clearly to senior leadership.

Market data and intelligence

·         Source, curate and maintain market data and market intelligence for use across the group, with clear ownership of data feeds, history, definitions and quality controls.

·         Maintain structured databases of vessel values, transaction activity, charter rates etc.

·         Produce market intelligence insight for senior management.

Digitalisation, automation and AI

·         Critically review how functions across the group work (processes, spreadsheets, models and handoffs) and challenge practices that are manual, duplicated, slow or no longer fit for purpose.

·         Identify, prioritise and automate manual processes across the group by modernising models and workflows in operating functions.

·         Lead change through to adoption, working with divisional heads to redesign processes, retire legacy tools and embed new ways of working.

·         Build analytical tools and data products that operating functions use day to day.

·         Embed AI and automation across the business with clear use cases, controls and measurable benefits.

·         Ensure every solution is tested, documented and handed over, so that it is reliable, easy to use and supportable.

Data foundations and governance

·         Work with the Head of IT to define the data architecture and a single source of truth for core operational and financial data.

·         Set data quality standards and data governance, including ownership, definitions and access.

·         Integrate internal and external data sources, including market data, into group data platforms.

·         Ensure that tools and data meet the company’s data security, access and privacy requirements.

3. Leadership and people

The Head of Analytics leads, builds and develops the Analytics team across the global offices, and acts as the group’s champion for data-driven ways of working.

·         Lead and develop the team, re-skilling towards data engineering, BI and automation where needed.

·         Build a team operating model with clear ownership, trackers and a regular cadence of reviews.

·         Raise data literacy and self-service use of data and tools across the wider business.

·         Set development objectives and plan future hiring against the digital roadmap.

·         Coach and mentor team members and support their career development, including rotation across areas of work.

·         Promote sharing of tools, methods and best practice across the Analytics team and the wider group.

·         Drive adoption of new tools through training, guidance and a clear launch process.

4. Candidate profile

Essential

·         Bachelor’s degree in Finance, Economics, Mathematics, Statistics, Engineering, Computer Science, Shipping or a related discipline; a postgraduate qualification or CFA is an advantage.

·         10+ years of experience in analytics within shipping, maritime, logistics, commodities, energy, or other asset-intensive industries.

·         A strong technical analytics background, with hands-on proficiency in advanced Excel, Power BI and data modelling.

·         Advanced financial modelling and valuation skills, with proven experience in transaction analysis, including building valuation, scenario and sensitivity models that support investment and transaction decisions.

·         Practical experience applying automation and AI tools to analytics and business workflows.

·         A track record of delivering digital transformation, from roadmap to adoption, and of leading change: challenging established processes, winning support for new ways of working and seeing change through.

·         The ability to translate business needs into technical requirements and data products that are used and trusted.

·         A critical, inquisitive mindset, comfortable questioning the status quo.

·         Strong stakeholder management and excellent communication and influencing skills, with the confidence to challenge senior leadership and explain complex analysis in plain terms.

·         Experience leading distributed, multi-location teams.

Desirable

·         Experience across multiple shipping sectors (e.g. tanker, dry bulk, gas or offshore).

·         Exposure to building or scaling an analytics or data function.

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