Data Scientist

Montoux’s modern cloud-based platform gives the world’s leading life and health insurers a scalable high-performance compute engine, sophisticated model-building capabilities, and a beautiful web-based user experience that provides radically improved insights into their products, pricing, and market dynamics.

We offer a fun and refreshing alternative to traditional corporate work environments. You will be part of a growing, talented, and supportive team where your ideas are genuinely valued. Our workplace offers flexible working and autonomy in your work. We embrace our culture of working closely together in a supportive way, recognizing that we grow our business by solving our customers' problems.

We're looking for a skilled, diligent and friendly data scientist to join our fast-moving team, which is spread across New Zealand and the US. You will work alongside our data scientists, actuaries and engineers to provide statistical insights, research the application of algorithms for proof-of-concept projects and deliver spike solutions for data processing, propensity modelling or visualization.

Type of work you will be involved in:

• Work with our actuarial team to understand our customers’ problems and develop solutions
• Customer data onboarding and exploratory data analysis
• Support R&D of inferential and predictive models round claims management, sales and pricing
• Customize and deploy computational price optimization methods
• Package these methods for efficient application for different customers
• Work with engineers to productionise these models and develop processes and tooling to do so
• Work with our Customer Success teams in New Zealand, US and Scotland to present findings and respond to customer questions
• Work within our data science team for code reviews, cross-team learning, mentoring and infrastructure decision making
• Potential for occasional domestic or international travel to meet with customers

Some of the tech we are using:

• Python & R on JupyterLab,RStudio and VSCode
• A wide range of AWS technology
• Statistical Analysis, Logistic Regression, Neural Networks, Optimization techniques
• R GLM modelling, scikit-learn, tensorflow, catboost, scipy-optimisation suite

Requirements

• Proven commercial experience in a data science/data analytics role
• Numerical/Statistical literacy
• Experience in developing both training and inference systems for machine learning pipelines
• An experienced programmer in at least one of Python/R on Unix/Linux systems
• Comfortable with AWS infrastructure, CI/CD tooling, and working on the command line
• Familiarity with distributed data systems
• Experience collaborating with and supporting the multidisciplinary team within a customer focused delivery environment
• Clear and concise communication, both written and oral, and the ability to advocate the current best practice to diverse set of stakeholders
• Experience in programming for reliability, availability, security and performance