Insurance Data Scientist: Predictive Analytics & Insights

Boardroom Appointments; Sandton; On-site; ZAR 600,000 - 850,000; Full time

Job summary

Boardroom Appointments sucht einen erfahrenen Data-Analysten, der aus Rohdaten geschäftlichen Nutzen ableitet. Sie sammeln Daten von mehreren Quellen, bereinigen sie und wandeln sie in verständliche Insights um, um Strategien zu unterstützen.

Sie arbeiten eng mit Kunden, Produktmanagern und Entwicklern zusammen und nutzen fortgeschrittene Statistik, maschinelles Lernen und Visualisierung, um Ergebnisse klar zu kommunizieren.

Qualifications

• Abschluss in Naturwissenschaften oder Ingenieurwesen mit Schwerpunkt Informatik/Statistik/Mathematik/Actuarial Sciences.
• Fließende Programmierkenntnisse in Python, SQL und R.
• Wünschenswert: Kenntnisse in C#.Net, C, C++, Visual Basic oder SQL.

Responsibilities

• Gewinn aus Daten durch systematische Analysen ableiten.
• Daten aus mehreren Quellen beschaffen und Umgebungen verwalten.
• Mit Kunden kommunizieren, um strategische Ergebnisse zu vermitteln.

Skills

Python

SQL

R

C#.Net

C

C++

Visual Basic

Education

Bachelor's degree in sciences/engineering

Job description

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.

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

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.

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.