Staff Data Scientist

United Kingdom

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Fintech, SaaS, PaymentsIndustries

Requirements

Candidates must have a proven track record of successfully deploying machine learning models into production environments and extensive experience with classical ML techniques such as boosted trees, neural networks, regressions, and clustering. Demonstrated expertise with agentic AI, prompt engineering, and leveraging Large Language Models (e.g., LangChain/Graph) is required, along with proficiency in Python and key data science libraries like Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch. An industry expert in model development, deployment, and MLOps practices is essential, alongside strong analytical and problem-solving abilities, sound business judgment, and excellent communication skills for engaging technical and non-technical stakeholders.

Responsibilities

The Staff Data Scientist will identify and drive new strategic opportunities through advanced machine learning models and analytics, such as pricing, support automation, and KYB automation. They will design comprehensive systems including data capture, operational processes, experimentation frameworks, and feedback mechanisms. Responsibilities include leading end-to-end model development and deployment processes using classical ML and LLM-based methods, collaborating across teams for seamless integration and productionization, and mentoring others on best practices. The role involves working with various teams to identify AI/ML opportunities for business value, conducting rigorous experimentation and validation, operationalizing data-driven solutions with cross-functional teams, and continuously monitoring and iterating on production models.

Skills

Machine Learning

Data Science

Pricing Optimization

Customer Support Automation

KYB Automation

Boosted Trees

Neural Networks

Regressions

Agentic AI

Large Language Models (LLM)

Experimentation Frameworks

Data Capture

Operational Processes

Feedback Mechanisms

Model Development

Model Deployment

Analytics

Paddle

Platform for SaaS billing and compliance

About Paddle

Paddle simplifies software sales for SaaS companies by providing a platform that manages billing, payments, tax compliance, and customer support. Its tools allow developers to focus on product development instead of administrative tasks. Paddle's all-in-one solution includes payment processing, subscription management, invoicing, and compliance with international tax laws, helping clients streamline operations and scale efficiently. The company earns revenue through transaction fees and subscription plans, aligning its success with that of its clients. Paddle's platform is flexible, easy to configure, and offers extensive API documentation for seamless integration. It also supports webhook notifications for real-time updates. The goal of Paddle is to be a vital partner for software companies aiming to grow internationally while managing the complexities of tax and compliance.

London, United KingdomHeadquarters

2012Year Founded

$283.4MTotal Funding

SERIES_DCompany Stage

Enterprise Software, FintechIndustries

201-500Employees