Data Scientist

Life Healthcare; Rosebank; On-site; ZAR 400 000 - 500 000; Full time

Job summary

A healthcare organization is seeking a Data Scientist to drive advanced analytics at their head office. The successful candidate will analyze data to extract insights that inform strategic decisions and enhance business value. Responsibilities include applying statistical and machine learning techniques, collaborating across teams, and presenting insights effectively. A Bachelor’s degree and at least 2 years of relevant experience are required, with a preference for candidates knowledgeable in Python, R, or SQL. Experience in healthcare is a strong advantage.

Qualifications

• Minimum Bachelors and preferably Honours-level degree in an analytical field.
• 2+ years of experience using statistical and machine learning techniques.
• Specific coding language experience (Python / R / SAS / SQL).
• Healthcare experience will be a strong advantage.

Responsibilities

• Drive business value through predictive and prescriptive analytics.
• Extract insights from structured and unstructured datasets.
• Collaborate effectively to solve analytical problems.
• Monitor the performance of advanced analytic models.

Skills

Statistical analysis

Machine learning

Python

R

SQL

Education

Bachelor's degree in Computer Science or related field

Honours-level degree preferred

Tools

Big data solutions

Job description

Function Information technology Facility Position Data Scientist Introduction

Two vacancies exist for Data Scientists based at Life Head Office in Dunkeld , reporting to the Statistician Leads . The successful candidate will be a key part of driving and embedding advanced analytics in the organisation. The role is responsible for extracting hidden insights from data that can inform strategic decisions using cutting-edge statistical and machine learning techniques.

Critical Outputs

• Ensure that Life Healthcare can drive business value through predictive and prescriptive analytics.
• Apply statistical and machine learning techniques to extract insights from structured and unstructured datasets to solve specific problems of business stakeholders.
• Identify opportunities for additional value-adding insights from data analysis.
• Ongoing skills development and research into optimal techniques and solutions for analytical problems.
• Work effectively independently and as part of a team collectively to solve problems.
• Present insights in a compelling and actionable way.
• Deliver insights that enhance business and senior management views of the value of analytics to the organisation.
• Use business knowledge and data understanding to extract features from raw data that can improve machine learning models
• Ongoing monitoring of the performance of advanced analytic models

Requirements

• Minimum Bachelors and preferably Honours-level degree in Computer Science, Mathematics, Statistics, Actuarial Science, Economics or a cognate analytical field, or other equivalent qualifications.
• 2+ years of experience in an analytics environment, using statistical and machine learning techniques.
• Commitment to continuous learning and sharpening of skills.
• Specific coding language experience (Python / R / SAS / SQL) would be an advantage
• Good communication skills.
• Understanding data architecture and pipelines and engaging effectively with the team responsible for ensuring that data delivery meets analytical needs.
• Demonstrated ability to analyse and interpret complex problems or processes that span multiple business areas, identify and understand requirements, and develop alternate solutions.
• Ability to translate complex analytical concepts into a digestible and understandable way for the business stakeholder.
• Ability to work to deadlines.
• Familiarity with relevant analytics tools, including big data solutions.
• Healthcare experience will be a strong advantage.

Competencies

• Attention to detail
• Analytical thinking
• Problem-solving, analysis and judgement
• Resilience
• Engaging diversity
• Analytical mindset
• Building relationships
• Customer responsiveness
• Organisational awareness
• Excellence orientation
• Deadline driven
• Professionalism