Job Specifications
We're seeking a Full Stack Data Scientist for GTM to own end-to-end data infrastructure, advanced analytics, and predictive modeling across our entire go-to-market organization. You'll architect and maintain the data ecosystem powering Marketing, Sales, and Customer Success—from raw data pipelines to production ML models that drive revenue growth. Reporting directly to Revenue Operations, you'll work alongside our VPs of Sales, Marketing, and Customer Success to transform GTM data into competitive advantage through robust infrastructure, predictive models, and AI-powered intelligence.
About the Team
You'll be embedded in our Revenue Operations team—the strategic engine accelerating growth by delivering operational excellence, data-driven decision frameworks, and cutting-edge AI tooling to Marketing, Sales, and Customer Success.
What You'll Own
Data Infrastructure & Engineering :
Design, build, and maintain end-to-end GTM data pipelines spanning lead capture through customer retention, ensuring data quality, governance, and accessibility across all revenue touchpoints
Architect scalable data models that unify marketing automation, CRM, product usage support, and billing data into a single source of truth for GTM analytics
Implement automated data validation and monitoring to ensure pipeline reliability and data integrity across all GTM systems
Collaborate with the 2 data squads (in our Product & Tech organization) to define and optimize the operating models for distributed governance and business performance, supporting real-time reporting and ML model training at scale
Predictive Modeling & Machine Learning :
Build, maintain, and continuously optimize in-house churn prediction models using gradient boosting, survival analysis, or deep learning approaches—leveraging customer behavioral data, product usage patterns, engagement metrics, and account characteristics to enable proactive retention strategies
Develop and deploy production ML models for lead scoring, conversion probability estimation, deal velocity forecasting, expansion opportunity identification, and customer lifetime value prediction
Create sophisticated time-series forecasting models for pipeline health, Gross Revenue Retention (GRR), Net Revenue Retention (NRR), and revenue predictions with confidence intervals and scenario planning capabilities
Implement advanced segmentation using clustering algorithms (k-means, DBSCAN, hierarchical clustering) to identify high-value cohorts, at-risk accounts, and expansion candidates
Design and execute A/B tests and causal inference studies to measure impact of GTM interventions on conversion rates, sales velocity, and retention metrics
AI Implementation & Advanced Analytics :
Collaborate with AI/ML engineers to productionize machine learning models—ensuring model monitoring, versioning, and continuous improvement
Apply NLP and text mining techniques to analyze sales call transcripts, customer communications, support tickets, and feedback for sentiment analysis, topic modeling, objection patterns, and success indicators
Build recommendation engines for next-best-action suggestions across sales plays, marketing campaigns, and customer success interventions
Implement anomaly detection systems to identify unusual patterns in pipeline health, customer engagement, or usage that signal risk or opportunity Business Intelligence & Strategic Insights
Design and maintain executive dashboards tracking full-funnel GTM performance: CAC, LTV, LTV:CAC ratio, MQL/SQL/SAL/QSO conversion rates, sales cycle length, win/loss rates, logo and net revenue churn, expansion revenue, and NPS/CSAT trends
Build automated reporting systems with drill-down capabilities by segment (FTE bands), service level (Premium/Core/Self-Serve), cohort, geography, and time period
Conduct rigorous statistical analyses including cohort analysis, attribution modeling, funnel optimization studies, and trend identification across the customer lifecycle
Perform root-cause analysis on performance anomalies, using statistical testing to validate hypotheses and separate signal from noise
Generate actionable insights that translate complex model outputs into clear business recommendations for GTM leadership
Why This Role Matters
You'll directly impact revenue growth by building the predictive intelligence and data infrastructure that enables our GTM teams to:
Generate higher-quality pipeline through ML-powered lead scoring and propensity modeling
Accelerate deal velocity with predictive insights on conversion probability and optimal sales plays
Reduce churn by 15-30% through early warning systems, survival models, and proactive intervention triggers
Maximize expansion revenue by identifying the right accounts at the right time with recommendation algorithms
Optimize resource allocation across marketing spend, sales capacity, and CS coverage using forecasting and simulation
This is a high-visibility role with direct access to exe
About the Company
Spendesk is the complete spend management platform that saves businesses time and money by connecting company spend.
With the integration of everyday technologies, built-in automation, and an easily adopted approval process, Spendesk's single solution makes agile, efficient spending easy for employees and gives finance leaders complete visibility across the entire company spend.
Trusted by thousands of companies, Spendesk is proud to have over 200,000 users across France, the UK, Germany and Spain.
Spendesk also puts c...
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