BI Data Scientist

Boardroom Appointments; Sandton; On-site; ZAR 600,000 - 900,000; Full time

Job summary

Boardroom Appointments in South Africa seeks a data scientist to leverage data to drive insights, inform decision-making, and enhance our life and non-life insurance operations. You will work with cross-functional teams to develop data-driven solutions, build predictive models, and implement BI solutions using SQL, ETL practices and Power BI, applying advanced statistical methods.

Applicants should hold a relevant degree and 4+ years in data science, with strong Python/R/Java skills and

Qualifications

• Bachelor's degree in informatics, CS, statistics, mathematics or IT.
• 4+ years in data science or similar role, preferably in life and non-life insurance.
• Proficiency in Python, R or Java; experience with ML libraries (TensorFlow, PyTorch, scikit-learn).
• Strong SQL/T-SQL experience; data modelling and experimental design knowledge.

Responsibilities

• Participate in analysis, design, development, troubleshooting and support of analytics platform.
• Analyze complex datasets to identify trends and correlations.
• Develop, implement and validate machine learning models.
• Build scalable data pipelines and BI solutions using MSBI stack.
• Collaborate with actuaries, underwriters, and stakeholders to integrate data science solutions.

Skills

Effective communication

Cross-functional collaboration

Problem solving

Data storytelling

Education

Bachelor's degree in Informatics/CS/Statistics/Math/IT

Tools

Python

R

Java

TensorFlow

PyTorch

scikit-learn

SQL Server

T-SQL

Power BI

Hadoop

Spark

Kafka

Azure

AWS

Job description

As a data scientist, you will play a key role in leveraging data to drive insights, inform decision-making, and enhance our life and non-life insurance operations. You will work closely with cross-functional teams to develop innovative data-driven solutions that address business challenges and improve overall performance.

Requirements

Bachelors degree/diploma in one of the following fields: Informatics, Computer Science, Statistics, Mathematics or Information Technology

Proven experience working as a data scientist or in a similar role, preferably in the life and non-life insurance industry

Proficiency in programming languages such as Python, R, or Java, as well as in data analysis and machine learning libraries (TensorFlow, PyTorch, scikit-learn)

At least 4 years working experience in the following:

Microsoft SQL Server (critical)

T-SQL (critical)

Effective communication skills, with the ability to collaborate with cross-functional teams and present complex ideas clearly and concisely

Strong understanding of statistical concepts, data modelling techniques, and experimental design principles

Duties and Responsibilities

Participate in the analysis, design, development, troubleshooting and support of the reporting and analytics platform

Analyze complex datasets to identify trends, patterns, and correlations

Generate and test working hypotheses and interpret results to provide actionable insights

Develop, implement and validate machine learning algorithms and statistical models

Build and operationalize predictive models to unearth hidden insights

Collaborate with actuaries, underwriters, and other stakeholders to integrate data science solutions into existing workflows and processes

Develop BI solutions using SQL, ETL scripting, business intelligence tools, database programming and reporting tools on the Microsoft BI Stack

Build scalable data pipelines and infrastructure for collecting, processing, and analyzing large volumes of structured and unstructured data

Automation of recurring processes and monitoring thereof

Must have prior experience developing business intelligence solutions in large or midsize companies

Must be able to manage multiple tasks simultaneously and react to problems quickly

Must have extensive experience with T-SQL

Must be able to develop, maintain, review, and explain predictive models

Understanding of the financial services industry desired, especially Insurance

Experience using data visualization tools, e.g., Power BI

Excellent problem-solving skills and the ability to translate business requirements into actionable insights

Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure, Google Cloud Platform)