Data Scientist

Role Purpose

Derive business value from data through systematic analysis and interpretation.

• Proactively source data from multiple suppliers and conduct advanced statistical and analytical work to extract actionable insights.
• Store and manage extracted data in appropriate internal or external environments, expanding database structures as needed.
• Engage with clients to communicate strategic results and insights.
• Apply advanced analytics technologies, statistical methods, and potentially machine learning and predictive modelling techniques.
• Communicate technical findings and methodologies effectively to both technical and business audiences.

Qualifications

• Bachelor's Degree in Sciences or Engineering with a strong focus on Computer Science, Statistics, Mathematics, or Actuarial Sciences.
• Fluency in Python, SQL, and R.
• Beneficial: fluency in C#.Net, C, C++, Visual Basic, or SQL.

Experience

• 3-5 years of experience in data warehousing, data sciences, and/or modelling environments.
• Strong understanding of software languages and software infrastructure.
• Proven experience in working with and analysing data.
• Insurance industry experience and actuarial background are advantageous.

Outputs Statistical and Mathematical Skills

• Predictive modelling skills.
• Knowledge and implementation of machine learning principles.
• Critical analytical thinking and attention to detail.

Programming and Technical Skills

• High-level proficiency in Python and SQL; experience with R and JavaScript.
• Understanding of cloud and web infrastructure.
• Experience deploying web applications to Azure (beneficial).
• Spark and version control experience.
• Data modelling, analysis, and loading from varied formats with awareness of data regulations.
• Consuming and validating data from multiple sources.
• Managing data version control and ensuring data integrity for auditing.
• Geo-spatial analysis.
• Using Business Intelligence tools (e.g., Power BI) to present insights.

Business Analysis

• Analyse and document processes that translate into deriving business value from data.
• Understand the insurance operational environment.
• Work with stakeholders to define business requirements for data presentation.
• Interpret reinsurance treaties in the context of specific data sets.

Interpersonal Skills

• Strong organisational and self-motivation skills.
• Ability to work independently and collaboratively across teams.
• Understand both technical and non-technical insurance concepts.
• Translate business and technical processes into clear documentation.

Competencies Data Wrangling

• Identify and treat imperfections in data (e.g., missing values, inconsistencies).
• Ensure data cleanliness and readiness for analysis.

Stakeholder Engagement and Teamwork

• Create a collaborative working environment.
• Engage effectively with software developers, product managers, and technical specialists.

Data Visualisation and Communication

• Communicate analytical findings and techniques to both technical and non-technical audiences.

Self-Awareness and Insight

• Build effective relationships, manage ambiguity, and provide perspective in challenging situations.

Software Infrastructure Building

• Set up data structures and environments to support analytical processes.

Diversity and Inclusiveness

• Engage respectfully and effectively with individuals from diverse backgrounds and cultures.

Data Intuition

• Identify and prioritise high-value business problems through data-driven insights.

Independence

• Take ownership and accountability for own actions and deliverables.

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