Data Scientist - Core Analytics - Remote

Overview

Ripjar specialises in the development of software and data products that help governments and organisations combat serious financial crime. Our technology is used to identify criminal activity such as money laundering and terrorist financing, enabling organisations to enforce sanctions at scale to help combat rogue entities and state actors.

Data infuses everything Ripjar does. We work with a wide variety of datasets of all scales, including an always-growing archive of 10 billion news articles in (nearly!) every language in the world going back over 30 years, sanctions and watchlist data provided by governments, plus 250 million organisations and ownership data from global corporate registries.

We have 2 core product offerings, Labyrinth Screening & Labyrinth Intelligence. Labyrinth Screening allows companies to monitor their customers or suppliers for entities that they aren’t allowed to or do not want to do business with (for ethical or environmental reasons). Labyrinth Intelligence empowers organisation to perform deep investigations into varied datasets to find interesting patterns and relationships.

This is a great time to join a growing group of highly talented technologists and data scientists who are building products that solve real world issues and are changing the way criminal activities are detected and prevented.

In Short

• Support the research, development, and ongoing maintenance of Ripjar's analytics and data products.
• Carry out data analysis tasks to develop Ripjar’s understanding of relevant data.
• Develop, evaluate and deploy machine learning models that integrate with Ripjar's software products.
• Work with Language models, machine learning tools and large-scale distributed clusters.
• Collaborate with Data Engineers to scale and integrate new analytics into products.
• Produce statistical tests and summarise outputs.
• Document analytics, models and methodologies.
• Provide support to stakeholders in understanding analytics and models.
• Support and maintain models in production.

Requirements

• Strong technical and theoretical background in data science.
• Proficient in at least one programming language, preferably Python.
• Good understanding of machine learning and large-scale data analysis.
• Experience with complex data at scale.
• Motivated and experienced in deploying data science products.

Benefits

• Work with a talented team of technologists and data scientists.
• Opportunity to solve real-world issues.
• Continuous innovation culture.