Job Description
About Nexcess Nexcess provides specialty cloud solutions for organizations where performance and compliance have to coexist. We serve businesses worldwide, from agencies scaling client sites to enterprises running mission-critical operations. We've built our reputation on deep technical expertise and genuine partnership with every client we work with. Behind every environment we manage is a team of people who take the craft seriously and keep showing up when it matters. About The Role Nexcess is hiring a Data Scientist to power our volumetric, subscription-driven growth engine (hosting, commerce, and software). This role owns the models and measurement systems connecting marketing spend to conversion, retention, and LTV, with a critical emphasis on ICP-specific economics (agencies, SaaS, ecommerce, and mission-critical buyers). You aren’t just a "dashboard builder." You are a Data Anthropologist. You look past the rows in Snowflake to see the human stories—the friction points that cause churn, the "aha" moments that trigger an upgrade from VPS to Dedicated, and the behavioral patterns that separate a hobbyist from a mission-critical enterprise buyer. You’ll build and operationalize LTV and churn models, develop marketing attribution approaches, and partner across Marketing, Product, RevOps, and Finance. You will also help hire and lead a reporting team, setting the standard for metrics, dashboards, and governance in Power BI. This Job Is For You If You speak "Finance" and "Creative" fluently. You can explain $LTV$ to a CFO and conversion attribution to a Copywriter without losing the soul of either. You are a "Pattern Hunter." You don't just report that churn happened; you find the "Silent Churn" indicators three months before the customer even thinks about canceling. You loathe "Vanity Metrics." You find no joy in "Total Page Views." You live for Contribution Margin and Cohort Payback Periods. You’re a Power BI Poet. Your DAX is elegant, your star schemas are pristine, and your dashboards tell a story so clear that an executive can understand the "Why" in under ten seconds. What You’ll Do Subscription Economics & LTV Modeling: Build predictive LTV models accounting for upgrades, churn, and margin. Develop payback and CAC views to support budget allocation and align with Finance on contribution LTV and time horizons. Expansion Strategy (Upsell & Cross-sell): Model the triggers and pathways for account expansion. Develop propensity-to-buy models for add-ons (security, storage, backups) and build data-driven upgrade paths (e.g., VPS to Dedicated) to maximize customer wallet share. ICP & Segmentation Modeling: Define and operationalize ICP segmentation using firmographic, behavioral, and intent signals. Create a decision framework to quantify ICP-specific retention, plan mix, and support costs. Attribution & Measurement: Design multi-touch attribution (MTA) models calibrated with incrementality methods like geo-tests and holdouts. Improve full-funnel measurement from first touch through activation and retention. Data Foundation & Reliability: Partner with Marketing Ops to ensure clean event tracking (GTM, dataLayer, UTMs). You'll be the guardian of the dataLayer, ensuring that what we see in GTM actually reflects reality in Snowflake. Power BI Reporting & Governance: Own executive-ready reporting, including KPI scorecards and cohort views. Maintain semantic models using DAX, ensuring star schema design, query folding, and incremental refreshes for scalability. Team Leadership: Help hire and coach a reporting and analytics team. Establish operating rhythms (WBR/QBR) and set standards for dashboard design, documentation, and storytelling. What Success Looks Like (6–12 Months) Liquid Web utilizes a defensible LTV and payback model for all spend decisions. LTV:CAC and payback are reported accurately by both ICP and channel. Expansion metrics (upsell/cross-sell velocity and attachment rates) are visible and actionable for Marketing and Sales. Power BI serves as the governed, trusted "source of truth" across the organization. Required Qualifications Experience: 5+ years in Data Science or Growth Analytics within a subscription-based business. Modeling: Proven track record building LTV, churn, and ICP segmentation models tied to revenue outcomes. Revenue Growth: Demonstrated ability to analyze and optimize upsell/cross-sell funnels and product attachment rates. Tech Stack: Advanced SQL and proficiency in Python/R. Expert-level Power BI (DAX and semantic modeling) and experience with Snowflake