Revenue & Predictive Analyst Intern (Summer 2026)

Spire•Washington, DC

4h•Hybrid

About The Position

We are offering a unique opportunity to learn Strategic Decision Support within the space and defense sector. You will work at the intersection of big data and federal policy, learning to build predictive models that identify where the market is moving before anyone else. This role provides a front-row seat to the Challenger Brand strategy, teaching you how to use data-driven insights to neutralize the advantages of larger legacy competitors. The Work Find the Undervalued Opportunities. Analyze Spire's historical win/loss data from Salesforce to identify the profile of a winnable federal opportunity Cross-reference against the full federal market: pull budget justification documents (P-40s, R-2s), GovWin pipeline, and SAM.gov awards to find opportunities that match the win profile but haven't been prioritized yet Flag undervalued targets with high win probability the team isn't currently focused on Deliver a force-ranked opportunity list with the analytical rationale behind every ranking Build the Revenue Engine Model Build a conversion model from Salesforce data, stage-by-stage probability, average cycle time, and deal velocity by agency type and capability area Produce a rolling revenue forecast by quarter, updated from live pipeline data Model the gap: if the target is $X, what qualified pipeline is required? What activity levels? What accounts? Decode the Federal Budget Map federal appropriations and program budget lines for Spire's capability areas Identify growing budget lines and declining ones where Congress and the Pentagon are putting money, and where are they pulling back? Surface emerging programs and new starts that align with Spire capabilities before a formal solicitation exists Deliver a budget signal report: the 10 federal programs where Spire should be investing time right now Know the Competition Map the competitive landscape by capability area, who is currently winning contract, programs and awards Pull SAM.gov contract award data to track competitor wins, contract values, and expiration dates Identify recompete targets: competitor-held contracts expiring in 12–24 months where Spire has a credible shot Build a one-page competitive brief per capability area: who we're beating, who we're losing to, and the analytical case for why we win the next one Tell The Story Behind the Data Every analysis must be delivered with a clear 'so what' the 3–5 decisions leadership should make based on what the data shows Present findings to Federal Sales leadership weekly, not as a data dump, but as a structured argument for where to focus and why All models delivered in Excel or Power BI, documented so they outlast the internship

Requirements

Currently enrolled in a bachelor's or master's program in Finance, Economics, Data Science, Statistics, Business Analytics, or a related quantitative field
Ability to work approximately 40 hours for the duration of the 8-week program
Exceptional analytical instincts
Strong Excel skills required; Python and Power BI are a significant plus
Ability to turn complex analysis into a clear, concise argument for a non-technical audience
Operates independently and moves fast

Nice To Haves

Prior experience with CRM data cleanup, Salesforce administration, or SharePoint management
Power BI or dashboard-building experience from coursework or a prior role
Familiarity with federal government or B2B sales environments
Evidence of building or owning a system

Responsibilities

Analyze Spire's historical win/loss data from Salesforce to identify the profile of a winnable federal opportunity
Cross-reference against the full federal market: pull budget justification documents (P-40s, R-2s), GovWin pipeline, and SAM.gov awards to find opportunities that match the win profile but haven't been prioritized yet
Flag undervalued targets with high win probability the team isn't currently focused on
Deliver a force-ranked opportunity list with the analytical rationale behind every ranking
Build a conversion model from Salesforce data, stage-by-stage probability, average cycle time, and deal velocity by agency type and capability area
Produce a rolling revenue forecast by quarter, updated from live pipeline data
Model the gap: if the target is $X, what qualified pipeline is required? What activity levels? What accounts?
Map federal appropriations and program budget lines for Spire's capability areas
Identify growing budget lines and declining ones where Congress and the Pentagon are putting money, and where are they pulling back?
Surface emerging programs and new starts that align with Spire capabilities before a formal solicitation exists
Deliver a budget signal report: the 10 federal programs where Spire should be investing time right now
Map the competitive landscape by capability area, who is currently winning contract, programs and awards
Pull SAM.gov contract award data to track competitor wins, contract values, and expiration dates
Identify recompete targets: competitor-held contracts expiring in 12–24 months where Spire has a credible shot
Build a one-page competitive brief per capability area: who we're beating, who we're losing to, and the analytical case for why we win the next one
Every analysis must be delivered with a clear 'so what' the 3–5 decisions leadership should make based on what the data shows
Present findings to Federal Sales leadership weekly, not as a data dump, but as a structured argument for where to focus and why
All models delivered in Excel or Power BI, documented so they outlast the internship