Data & Analytics Lead (Quantitative / Data Modeling Focus)- 12 Month Contract

THE ROLE

We’re seeking a Data & Analytics Lead with a focus on quantitative analysis and data modeling to design and operationalize a unified data framework that integrates financial, operational, and technical data across multiple systems. This role sits within the Global Value Management (GVM) team—an organisation focused on developing proactive, data-driven proposals and value propositions that help customers understand the business impact of our solutions.

This person will build the analytical foundation that powers GVM engagements, linking data insights to customer performance, opportunity sizing, and value realisation. The successful candidate combines strong data architecture and quantitative analysis skills with the ability to translate complex data into actionable business insights.

WHAT YOU'LL DO

Data Model & Architecture

• Define a master data model spanning financial, operational, and technical dimensions, including relationships and dependencies.
• Collaborate with Sales Operations to determine the right platform and integration architecture.
• Source and align data from multiple systems—Customer, Competitor, GVM Engagements, HGInsights, Marketing Ops (6Sense, Leadspace, Gartner, IDC), AlphaSense, and Snowflake.
• Develop a data confidence scoring model (validated, inferred, assumed) and processes for maintenance, expiry, and refresh.
• Define clear data governance rules, including ownership, quality standards, refresh cycles, and version control.

Analytics & Insight Generation

• Build relational data sets linking metrics such as $/TB and FTE/TB.
• Produce benchmarks, quartiles, and regression analyses to uncover performance drivers across cost, efficiency, and technical spread.
• Design outputs that highlight “best-in-class” performance by vertical or environment (Cloud vs On-Prem).
• Create searchable internal indices for GVM use cases (for example, where similar takeouts or use cases exist).
• Deliver insight models that validate assumptions, expose trends, and inform customer recommendations.
• Apply predictive and prescriptive analytics to recommend likely values and optimal ranges for missing or uncertain inputs.
• Embed the master data model into core workflows and provide interfaces so models can pull and refresh data in real time.

Customer & Opportunity Modeling

• Correlate customer data against the master model to assess confidence and identify gaps.
• Use analytics to infer likely ranges for missing data and map customers to best-in-class benchmarks.
• Load validated data into business case models to inform account planning and opportunity prioritization.

What Success Looks Like

• A reliable, scalable master data framework that informs GVM and customer strategy and serves as a single source of truth.
• Automated confidence scoring and refresh processes.
• Predictive and prescriptive analytics that estimate key values, recommend likely ranges, and guide opportunity sizing and customer value realization.
• Benchmarking frameworks that inform strategic decisions and account planning.
• A foundation for evidence-based, data-driven customer proposals.
• We are primarily an in-office environment and therefore, you will be expected to work from the {{OFFICE_LOCATION}} office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, Econom