Data Scientist

Overview Guardrisk is the undisputed market leader in cell captive insurance and risk solutions. We are renowned for our innovative approach to cell captive structures and other alternative risk transfer solutions for our clients. Guardrisk offers clients custom designed cover and is registered in South Africa as an insurer for all statutory classes of non-life and life insurance business. This role is for a Data Scientist who will derive business value from data and communicate insights to technical and business audiences. Role Purpose The primary purpose of the Data Scientist is to derive business value from data. The Data Scientist will proactively fetch information from multiple data suppliers and conduct sophisticated and systematic analysis to extract actionable insights. Data will be stored in appropriate environments, and database structures may need to be expanded. There may be client engagement to communicate strategic results. The role requires advanced analytics technologies and strong statistical methods, potentially including machine learning and predictive modelling. A solid understanding of statistics and data wrangling is required, along with software skills. The ability to communicate findings and working methods across technical and business audiences is important. Qualifications Bachelor’s Degree in sciences or engineering with a strong focus on computer science, statistics, mathematics and/or actuarial sciences Fluency in Python, SQL and R Beneficial: fluency in any of C#.Net, C, C++, Visual Basic, SQL Experience 3-5 years of experience in a data warehousing, data sciences and/or modelling environment Good understanding of software languages and software infrastructure Experience in working with and analyzing data Insurance Industry Experience and Actuarial background Duties & Responsibilities Statistical and Mathematical Skills Predictive modelling skills Knowledge of machine learning principles at a high level and ability to implement as needed Critical analytical thinking and attention to detail Programming and Cloud/Web Infrastructure R, SQL, Python and JavaScript experience; high proficiency in Python and SQL Beneficial to have experience deploying web applications to Azure Spark experience Version control principles Data Modelling and Data Quality Data modelling, analysis and loading data from various formats; awareness of personal data regulation Consuming data from files/databases or online sources Validating data from multiple sources Data version control and data integrity for auditing Geospatial Analysis Using Power BI or similar BI tools to generate insights Business Analysis Analyze and document processes to derive value from data Understand the insurance operational environment Interpersonal Skills Self-organization and the ability to work independently when needed Collaborate with stakeholders across multiple technical areas Understand insurance concepts at a high level (technical and non-technical) Break down insurance processes and document as business requirements for data presentation Interpret reinsurance treaties in the context of individual data sets Competencies Data Wrangling: handle messy data, address imperfections, and enable data cleanliness Stakeholder Engagement and Teamwork: collaborate across the business with software developers, product managers and technical specialists Data Visualization & Communication: convey findings to technical and non-technical audiences Self-Awareness and Insight: manage ambiguity and pressure with perspective Software Infrastructure Building: set up data structures internally or externally Diversity and Inclusiveness: respect differences and engage diverse backgrounds Data Intuition: infer insights from large data sets and identify high-value problems Independence: take ownership for actions Location and Application Enquiries: Job Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology #J-18808-Ljbffr