Principal Data Scientist

🔥 35 minutes ago

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Provenir

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2004

☁️ SaaS

💳 Fintech

🤖 Artificial Intelligence

SaaS • Fintech • Artificial Intelligence

Provenir is the Decision Intelligence Platform for financial services providers. It offers a low-code, cloud-native SaaS platform that consolidates data, AI models, analytics and decisioning agents into a single governed environment to support credit risk, fraud & identity, compliance, onboarding, customer management and collections. The platform provides real-time, AI-powered decisioning, a data marketplace for identity/fraud/credit data, case management, and tools for deploying, validating and optimizing models and policies across global markets. Provenir is used by banks, credit unions, fintechs, payments and telco customers and processes billions of decisions annually.

📋 Description

• Own the strategy and build of our identity graph and graph-driven identity intelligence • Design and evolve a deterministic identity graph that represents key entities, relationships, and business logic • Identify and prioritise the features, signals, and patterns in our connected data that create product value • Build and guide analytics pipelines for link analysis, identity resolution, clustering, ranking, anomaly detection, and discovery • Partner with data engineers to define ingestion, enrichment, validation, and publishing workflows into the identity data • Work with product managers and stakeholders to translate ambiguous business problems into product features • Prototype and evaluate approaches for identity resolution, identity intelligence, fraud detection, and risk intelligence • Partner with data engineers to define the quality and coverage signals that matter for trustworthy identity intelligence — coverage, match confidence, and accuracy • Select the right technologies and patterns, and create clear documentation and decision frameworks so the work can be reused across teams • Mentor engineers and data scientists on graph methods, modelling, and analytical techniques and grow a team as value is proven

🎯 Requirements

• Strong experience in graph data science, knowledge graphs, or graph/network analytics • Hands-on experience building and working with graph structures using libraries or databases (e.g. Neo4j, Amazon Neptune, JanusGraph, GraphFrames, NetworkX, or similar) • Experience with identity resolution, entity resolution, or link analysis • Strong Python and SQL skills • A genuine product mindset, you start from the business problem and the product outcome, not the technique, and you can prioritise accordingly • Ability to design analytical approaches from ambiguous problems • Track record of operating in production environments with quality, scale, and reliability requirements • Strong communication skills and comfort working embedded with product and engineering teams • Although not essential, it would be great if you have experience with: • Building graph-enabled products in identity, fraud, financial crime, risk, or AI-driven decisioning • Graph embeddings or other graph-native ML methods • Ontology design, semantic modelling, or taxonomy development • Large-scale distributed data processing (e.g. Spark, Dask) • Building and growing data science teams • Working in scale-up or early-stage environments

🏖️ Benefits

• Health Plans • WFH allowance • Macbook Pro • Comprehensive private health cover and wellness plans • Flexible and remote-friendly opportunities • Maternity/paternity leave • Retirement benefits such as pension contributions to plan for your future