Who We Are

Provenir is a global fintech company with offices across North America, the UK, and Singapore. Provenir helps fintechs, financial institutions, and payment providers make smarter decisions, faster. We are passionate about technology and empowering businesses to become industry leaders. As a leading provider of decisioning and analytics products for financial services and other industries, we empower businesses to create digital-first decisioning solutions that drive business growth. If you’d like to work at an innovative fintech with a global footprint that is redefining the industry, then we want you!

AI Innovation & Research Role

We are looking for a commercially minded expert in Data Science and Machine Learning to work closely with our Product and Technology teams to allow us to develop, improve and innovate on our use of advanced analytical approaches within our software products.

Provenir is a market leading solution for Credit Risk, ID and Fraud use cases across Financial Services - industry knowledge is useful but not required - the ability to pick up new topics quickly and apply technical concepts to business problems is the heart of this role.

Day-to-Day

• Interface with stakeholders within the business to understand analytical requirements and opportunities
• Research new machine learning algorithms and statistical techniques to solve problems in the detection and prevention of financial risk
• Contribute to the productionisation of new analytical features through prototyping, requirements setting and implementation
• Provide expert input into future analytical strategies and product development
• Share knowledge of analytical techniques and tooling across engineering and wider business teams
• Developing statistical models and algorithms for integration with Provenir products
• Working with development teams to support and enhance the analytical infrastructure
• Working with QA teams to advise on effective analytical testing

Technical Experience

• Knowledge of algorithms such as LGBm, decision trees, XGBoost, K means anomaly detection, Bayesian theory, etc.
• Understanding of evaluation and explanation techniques in machine learning, e.g., overfitting, bias, cross-validation, LIME, SHAP, etc.
• Experience and proficiency with Python and machine learning tools libraries like scikit-learn, pandas, numpy, etc, and statistical packages, e.g., Scipy

Our employees are our top priority, we offer comprehensive health and wellness plans. You will enjoy paid time off and company holidays, flexible and remote-friendly opportunities, and maternity/paternity leave.