Senior Data Scientist - Advanced Analytics

Who We Are Singulier is a strategy and transformation consulting firm working with private equity funds and their portfolio companies on high-impact digital, data and AI topics. We help investment funds, CEOs and leadership teams answer critical strategic questions and drive transformation with a pragmatic, hands-on approach. Unlike traditional consulting firms, we do not stop at recommendations: we work alongside our clients to design, build and implement solutions that create measurable impact.  Founded in 2017, Singulier has grown rapidly and now brings together ~80 professionals across Paris, London and Munich, combining expertise in strategy consulting, data, digital marketing, product and technology. 

The Role At Singulier, our Senior Data Scientists / Analysts turn complex data into the models that underpin our clients’ strategic decisions. You are the technical owner of advanced analytics on our engagements — designing, building and validating the models, and making their results legible to senior, non-technical audiences, including C-level executives and PE operating partners.  Customer and value analytics is the core of what we do, but the role is not limited to it: you will also tackle broader advanced-analytics questions, for example supply chain, demand planning and operational performance, including in industrial settings.  You work hand in hand with our consultants: they frame the business question, you bring the methodological depth to answer it rigorously. You care as much about the robustness of a model as about whether its output actually changes a decision — we value pragmatic, business-oriented work over purely academic or research-focused approaches. 

What You’ll Do • Design, build and validate advanced models — customer & value segmentation, propensity and churn scoring, uplift, LTV and pricing, as well as demand forecasting, supply chain and operational optimization  • Own the analytical methodology on engagements and guarantee statistical robustness  • Dive into raw client data: explore large, complex and sometimes messy datasets to understand how to extract value from the data  • Work hands-on with data: conduct data transformation, feature engineering and modelling in Python and SQL to build analytics-ready datasets  • Translate model outputs into clear, executive-ready findings and co-present to C-level stakeholders and investment funds  • Build and orchestrate AI agents to automate and scale recurring, repeatable analyses   • Write clean, reusable, well-documented code and contribute to the practice’s analytical toolkits and standardised analyses  • Prepare models and specifications for industrialisation, in handover to our Graphite data engineering team  • Act as the data science referent of the practice, supporting and upskilling consultants and analysts  • Explore and bring in new methods and AI / GenAI techniques where they add real value 

Our Stack We like experimenting with new technologies, but our core stack currently includes:  🧰 Databricks (Python / Pyspark)   🌐 Google Cloud Platform   ✨ N8N for AI agent workflows