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

Were in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here you lead with innovative thinking grow along with us and join the smartest team in the industry.

This type of workwork that changes the worldis what the tech industry was founded on. So if youre ready to seize the endless opportunities and leave your mark come join us.

THE ROLE

Were 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) teaman 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 YOULL 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 systemsCustomer 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 OFFICELOCATION office in compliance with Pures policies unless you are on PTO or work travel or other approved leave.

WHAT YOU BRING

Qualifications

• Bachelors or Masters degree in Data Science Statistics Computer Science Engineering Economics or a related quantitative field.
• 1 years experience in data analytics data modeling or quantitative analysis ideally in a B2B or enterprise technology environment.
• Proficiency in SQL Python/R and BI tools (Tableau Power BI or similar).
• Experience designing data models and pipelines across multi-source systems (for example CRM Marketing Ops Financial Systems).
• Strong understanding of data governance normalization and confidence scoring techniques.
• Demonstrated ability to synthesise large complex datasets into actionable insights.
• Excellent collaboration skills with cross-functional teams including Sales Finance and Operations.

Preferred Experience

• Background in enterprise data architecture or quantitative strategy consulting.
• Familiarity with Snowflake Salesforce and marketing intelligence or industry insights platforms (6Sense Leadspace HGInsights etc.).
• Experience with regression modeling clustering and multivariate analytics.
• Understanding of financial modeling cost analysis and performance benchmarking.

Master Data Role Detail

Key Objectives

Collation

• Define a data model of key types (tables) and data features (attributes) to collect spanning financial operational and technical scope.
• Define the data dependencies and relationships between them.
• Partner with Sales Operations to determine the platform this should be built on.
• Source multiple potential data records including:
• Customer
• Competitor
• Account team
• GVM (Engagements)
• HGInsights
• Marketing Ops data (6Sense Leadspace Gartner IDC etc.)
• Past Value and Install Base (Skyline)
• Win/Loss
• AlphaSense
• Other data in Snowflake
• Map data sources to the master data model.
• Define and build a confidence factor rating on the data (customer validated vs market data vs assumption).
• Define a model to maintain and update data sources.
• Set expiry dates on data.

Analytics

• Build relational tables that index data sources based on their dependencies (for example $/TB FTE/TB).
• Produce quartiles and ranges of confidence factors based on indexed data sources.
• Design and build insight reports that correlate attributes to performance for example:
• Overall cost related to technical spread (size utilisation etc.) and operational costs/performance.
• Operational efficiency relative to cost.
• Technical debt relative to cost and operational cost/performance.
• Cloud vs On-Prem.
• Locations/FTEs per scope or location.
• Design outputs to show best-in-class operating technical and financial performance attributes with variation by vertical industry.
• Create a searchable internal index for the GVM team (for example where a PowerFlex takeout has been done previously).
• Build a referenceable index (for example $/TB FTE/TB in a given industry based on historical GVM experience).
• Develop benchmarking to provide ranges and comparisons across data sets to assess whether assumptions are reasonable.
• Use regression analysis to identify trends in the data and uncover patterns that were not previously considered.

Customer Opportunity Sizing Validation and Testing

• Map available customer data (direct or indirect) to the master data model.
• Produce analytics to validate customer data against the master data and map to confidence factors (for example whether known size and cost are within the range of master data sources).
• Use predictive and prescriptive analytics to recommend likely ranges of values for missing data based on master record dependencies (for example for 5 FTEs in Operations costs are likely in range XY).
• Produce analytical outputs that map the customer to a best-in-class model.
• Load financials into the as-is business case model.
• Embed the master data model into GVM workflows with standardised interfaces and query access so models can pull refresh analyse and retrieve data in real time.
• Use these insights to inform account planning including estimating opportunity size and identifying high-potential opportunities.

#LI-ONSITE

WHAT YOU CAN EXPECT FROM US:

• Pure Innovation: We celebrate those who think critically like a challenge and aspire to be trailblazers.
• Pure Growth: We give you the space and support to grow along with us and to contribute to something meaningful. We have been Named Fortunes Best Large Workplaces in the Bay Area Fortunes Best Workplaces for Millennials and certified as a Great Place to Work!
• Pure Team: We build each other up and set aside ego for the greater good.

And because we understand the value of bringing your full and best self to work we offer a variety of perks to manage a healthy balance including flexible time off wellness resources and company-sponsored team events. Check out for more information.

ACCOMMODATIONS AND ACCESSIBILITY:

Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this contact us at if youre invited to an interview.

OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM:

Were forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isnt just accepted but embraced. Thats why we are committed to fostering the growth and development of every person cultivating a sense of community through our Employee Resource Groups and advocating for inclusive leadership.

Pure is proud to be an equal opportunity and affirmative action employer. We do not discriminate based upon race religion color national origin sex (including pregnancy childbirth or related medical conditions) sexual orientation gender gender identity gender expression transgender status sexual stereotypes age status as a protected veteran status as an individual with a disability or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire.

JOIN US AND BRING YOUR BEST.

BRING YOUR BOLD.

BRING YOUR FLASH.