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 executive leadership and the opportunity to shape how we leverage data science and AI across our entire revenue engine

What you Bring

Technical Foundation :

● Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Physics, or quantitative field (PhD preferred but not required)

● 4+ years of hands-on data science experience in revenue operations, GTM analytics, or business intelligence—preferably in B2B SaaS

● Expert-level SQL for complex analytical queries, window functions, CTEs, query optimization, and data modeling

● Strong Python or R programming for data manipulation (pandas, numpy, dplyr), statistical analysis, and ML model development

● Proven experience building and deploying predictive models in production—particularly churn prediction, propensity scoring, forecasting, or recommendation systems with measurable business impact

As we are an international team, please submit your application and CV in English.

About Spendesk
Spendesk is the AI-powered spend management and procurement platform that transforms company spending. By simplifying procurement, payment cards, expense management, invoice processing, and accounting automation, Spendesk sets the new standard for spending at work. Its single, intelligent solution makes efficient spending easy for employees and gives finance leaders the full visibility and control they need across all company spend, even in multi-entity structures. Trusted by thousands of companies, Spendesk supports over 200,000 users across brands such as SoundCloud, Gousto, SumUp, and Bloom & Wild. With offices in the United Kingdom, France, Spain and Germany, Spendesk also puts community at the heart of its mission.

For more information: www.spendesk.com/press

About our people & culture
We believe that people do their best work when they’re given the freedom to thrive and grow. That’s why liberation is at the core of everything we do. We empower Spendeskers to take ownership of their work, to navigate ambiguity, and seize every opportunity. Spendeskers come from all over the world (35+ countries and counting!) but we have plenty in common: we're bold, ever-curious, committed to kindness, and tackle every challenge with a positive mindset.

About our benefits
Our culture is built on trust, empowerment, and growth — with benefits to match!

• Flexible on-site and remote policy

• Latest Apple equipment — the tools you need to excel

• Access to Moka.care — for emotional and mental health wellbeing

• Great office snacks — to fuel your day

• A positive team to work with daily!

We also offer location-specific benefits tailored to each market, including health insurance, wellness allowances, commuter support, meal vouchers, and gym memberships — ensuring you're well supported wherever you're based.

Diversity & Inclusion

At Spendesk, we're committed to fostering an environment where all differences are encouraged, supported and celebrated. We're building our culture for everyone, with everyone. Our goal is to attract and build a diverse, equal and inclusive team, where everyone feels welcome and we truly embrace and encourage people from all backgrounds to apply.