Job Description & How to Apply Below
The Role
This role is focused on enabling better decision-making across the organization through high-quality analysis and the thoughtful application of AI and advanced analytics. You will work closely with Product and Engineering to improve how we understand platform usage, performance, and outcomes, and to shape product direction through data.
This is a hands-on leadership role. You will define how analytics operates identify high-impact opportunities and deliver meaningful analysisyourself. You will also play a key role in identifying and applying AI capabilities, particularly where they can unlock new product value or significantly improve internal decision-making.
Given the natureof data products, experience working with financialor market data is highly advantageous.
Key Responsibilities
Establish the Analytics Function
Define a vision, scope,and operating model for internalanalytics in collaboration with the VP Data and Analytics.
Identify high-impact opportunities where better data and analysis can materially improve business and product outcomes.
Establish best practices for analysis, experimentation, metric definition, and insight communication.
Build trust in analytics through rigor, clarity,and transparency. Product & Engineering Partnership
Partner closely with Product Manager sand Engineering Leads to supportroadmap decisions with data.
Support the definition and refinement of product metrics,KPIs, and success criteria.
Translate ambiguous product and system questions into structured analytical approaches.
Support experimentation and hypothesis-driven product development. Data Exploration & Analysis
Work across multiple system sand data sources(including SaaS platforms, APIs, and operational databases) to discover and extract relevant data.
Write queries and scripts to retrieve, combine,and prepare data for analysis.
Build robust, analysis-ready datasets across structured and semi-structured data.
Identify gaps in instrumentation, tracking, and data availability, and work with engineering to address them.
AI & Advanced Analytics Application
Identify opportunities to apply AI and machine learning techniques to improve product functionality, internal workflows, and decision-making.
Prototype and evaluate AI-driven solutions (e.g. LLM-powered analysis, classification, summarisation, anomaly detection).
Work with Engineering to integrate AI capabilities into products or internal tools where appropriate.
Stay current with emerging AI capabilities and assess their practical application within company Data and Analytics domain.
Balance experimentation with pragmatism, focusing on real business impactover technical novelty. Insight Generation & Decision Support
Conduct exploratory and deep-dive analysis to uncover trends,risks, and opportunities.
Apply appropriate statistical methods to ensure robust and reliableconclusions.
Translate analysis into clear,actionable recommendations for both technical and non-technical stakeholders.
Develop dashboards or lightweight reporting where appropriate, with a focuson meaningful and decision-relevant metrics.
Grow &Scale the Capability
Expand analytics supportbeyond Product & Engineering over time.
Coach and mentor team members,helping to raise the overallanalytical capability of the organisation.
Define future hiring needs and contribute to building a scalable analytics and AI function.
Essential Criteria
Significant experience in productanalytics, decision science,or data sciencewithin a SaaS or technology environment.
Proven experience partnering closely with Product and Engineering teams.
Strong SQL skillsand experience working with large-scale datasets.
Experience writing scripts(e.g. Python, Spark or similar) to retrieve, combine,and analyse data.
Strong statistical reasoning and ability to apply appropriate analytical methods.
Experience applying AI/ML techniques to real-world businessor product problems(e.g. predictive modelling, NLP, or LLM-based applications).
Familiarity with modernAI tooling and frameworks (e.g.Python ML stack,LLM APIs, or similar).
Ability to rapidly prototype and evaluate AI-driven approaches, and communicate their value and limitations to stakeholders.
Demonstrated ability to translate ambiguous business problems into structured, data-driven analysis.
Excellent communication skills,with a focus on influencing decisions and drivingaction.
Comfortable operating independently and setting direction in an emerging or evolvingfunction.
Desirable Criteria
Experience in financial services, particularly…
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