Head of Data Science

Our client is on a mission to redefine how trust is established in B2B relationships. As a fast-growing commercial risk data and analytics company, their proprietary platform gives businesses unmatched visibility into 20M+ U.S. businesses by blending leading public and regulatory sources with exclusive, peer-contributed data — powering smarter decisions across customer acquisition, underwriting, fraud prevention, and portfolio monitoring.

Analytic Product Development

• Own end-to-end development of analytic products—from raw data ingestion to scalable, production-ready outputs

• Design and iterate on features, attributes, and models that convert proprietary data assets into differentiated, commercial products

• Partner with Product and Engineering to ensure solutions are robust, scalable, and embedded into workflows

Scorecard & Attribute Development

• Design, build, and refine risk scores and predictive attributes across multiple use cases

• Manage and maintain multiple scorecard versions simultaneously

• Produce clear, audit-ready documentation of model methodologies to support client compliance and transparency

Machine Learning & Data Science Execution

• Develop and deploy machine learning models using Python, SQL, and modern ML frameworks

• Conduct exploratory data analysis to identify trends, signals, and opportunities

• Ensure data quality through rigorous preprocessing, validation, and monitoring

• Collaborate with data engineering to build scalable pipelines and support production ML workflows

Alternative Data Strategy

• Lead ingestion and productization of external and alternative data sources (e.g., cash-flow data, commerce platforms, vertical SaaS systems)

• Translate raw external data into structured attributes and predictive signals beyond traditional bureau data

• Identify new data partnerships that expand the organisation's data moat and product capabilities

Proof of Concept (POC) Delivery

• Partner with go-to-market teams to design and execute analytical POCs for prospective clients

• Translate client use cases into compelling, data-driven demonstrations that accelerate sales cycles

• Rapidly prototype and iterate models to showcase measurable value

Required Qualifications

• Advanced degree in Computer Science, Statistics, Mathematics, or related field

• 5–7+ years of experience in data science, including leadership responsibilities

• Deep expertise in machine learning, statistical modeling, and predictive analytics

• Strong hands-on proficiency in Python and SQL

• Proven experience building and deploying models at scale

• Demonstrated success developing risk scores, attributes, and scorecards (including version management)

• Experience working with alternative/non-bureau data sources (e.g., cash-flow, merchant, or platform data)

• Strong attention to detail, particularly in model documentation and compliance requirements

• Excellent communication skills, with the ability to translate complex concepts into business value