Data Scientist Sandton

Integrita Group; Gauteng; On-site; ZAR 400,000 - 500,000; Full time

Job summary

A leading company in the healthcare industry is seeking a Data Scientist to enhance data-driven decision-making across various business functions. The ideal candidate will possess a strong academic background, rich experience in applying data science techniques, and be adept at collaborating with stakeholders. Responsibilities include developing predictive models, engaging with business problems, and ensuring compliance with professional standards. This role provides a dynamic opportunity to impact healthcare outcomes through analytics.

Benefits

Medical aid

Pension Plan

Qualifications

• Minimum of 5-6 years' experience in data science.
• Experience operationalising data science solutions in a high-scale production environment.
• Familiarity with any machine learning ecosystem tools.

Responsibilities

• Support data-driven measurement and decision-making within various business functions.
• Collaborate with stakeholders to define business problems and develop strategies.
• Implement and monitor predictive models on large datasets.

Skills

Data Science

Machine Learning

Statistical Analysis

Data Visualization

Data Mining

SQL

Python

Predictive Analytics

Education

Degree (Honours, Masters, or PhD) in Statistics, Computer Science, Engineering, Mathematics

Relevant data science certifications

Tools

Python

Microsoft ML

Hadoop

AWS

NumPy

pandas

Jupyter Notebooks

Job description

Data Scientist The Data Scientist will support the Data Science and Analytics team in creating and enabling data-driven measurement, insights, monitoring, and decision support.

This individual will add value to business areas by providing insights, applying data science to inform and optimise decision making, and building automated predictive and prescriptive analytics solutions that support various business functions and address healthcare challenges.

The role requires involvement in the whole data science development process, including gaining a business understanding, defining the problem, data cleansing and feature engineering, business modelling and simulation, hypothesis generation and testing, machine learning model training, testing and refinement, and finally deployment and monitoring of predicted outcomes within the business solutions.

Duties & Responsibilities Identify and test innovative data science techniques that can be utilised in predictive analytics solutions across the Company.

Assist with research on trends in Data Science, specifically for the application in the healthcare industry.

Engage with business stakeholders in the discovery process to identify the business problem / opportunity, elicit requirements, and discuss the expected outcomes of modelling / solutions.

Partner with business stakeholders to define approaches to resolving key business problems and focus on the development of new business strategies.

Assist in developing conceptual designs or models to address business requirements.

Collaborate with subject matter experts to select the relevant sources of data and understand the business requirements to ensure that the models are delivered in an appropriate manner.

Partner with the Data Engineering team to obtain internal and external information and manage data utilisation.

Perform pre-processing of data which includes tasks such as data manipulation, transformation, normalisation, standardisation, visualisation, and features engineering.

Review existing data analytics solutions (code and / or models), measure quality, and identify potential improvements.

Use data profiling and visualisation to understand and explain data characteristics that will inform modelling approaches.

Identify and implement the appropriate data mining / statistics / machine learning techniques.

Implement predictive models on large datasets (including distributed parallel computation platforms such as Spark).

Perform business modelling that translates decisions and business processes into a computational model.

Validate and test analysis / models using appropriate techniques (back testing, A / B testing, scenario modelling, etc.).

Implement models using Company standard processes and techniques.

Monitor and maintain models with specific focus on model performance and the results being fit for purpose.

Ensure full compliance to statutory regulations, policies, procedures, best practice, and professional standards in line with the Company strategy.

Review and update all policies relating to data science.

Communicate findings to business with various skill levels and in various roles, presenting trends, correlations, and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights and defends recommendations.

Generate concise reports with relevant visualisations and commentary for management.

Desired Experience & Qualification Education Degree (Honours, Masters, or PhD) in Statistics, Computer Science, Engineering, Mathematics and / or a combination of these.

Relevant data science certifications such as Python, Microsoft, AWS, Hadoop, big data, machine learning, cloud infrastructure.

A minimum of 5-6 years' experience in data science related projects.

Experience with Python / Microsoft ML and tools available within the machine learning ecosystem (i.e.

NumPy, pandas, matplotlib, SciPy stack) and working in Jupyter notebooks.

Experience with SQL and working with large-scale data sets.

Knowledge and practical experience applying machine learning techniques.

Experience working in agile development teams.

Experience in operationalising data science solutions or similar product development.

Experience in a high-scale production environment is critical.

Package & Remuneration R60 – R66 pm CTC Medical aid + Pension included #J Ljbffr