Data Scientist – Itonga Resourcing Johannesburg

Data Scientist Vacancy in Johannesburg

Itonga Resourcing is recruiting an experienced Data Scientist for an opportunity in Johannesburg, Gauteng. The successful candidate will work in an enterprise technology and analytics environment, using data science and machine-learning techniques to solve complex business problems.

This opportunity is particularly suited to someone with practical experience in Python, R and/or SQL who can work with large datasets, develop predictive models and translate complex analytical findings into useful business insights.

Key Responsibilities

The Data Scientist will analyse large and complex datasets to identify trends, relationships, patterns and potential business opportunities.

Key responsibilities include:

• Applying data science and machine-learning techniques to business problems.
• Developing predictive and statistical models.
• Performing exploratory data analysis and data mining.
• Building, testing, validating and improving machine-learning models.
• Applying supervised and unsupervised learning techniques.
• Performing feature engineering and feature selection.
• Developing predictive solutions using historical and real-time information.
• Evaluating model performance and identifying opportunities to improve accuracy.
• Working with structured and unstructured datasets.
• Cleaning, transforming and validating data before analysis and modelling.
• Translating analytical results into useful business recommendations.
• Working with large-scale datasets and big-data technologies.
• Supporting the deployment and operational use of machine-learning models.
• Monitoring models after deployment and identifying optimisation opportunities.
• Documenting models, assumptions, methodologies and results.

Machine Learning and Data Science Skills

Candidates should have practical experience across areas such as:

• Machine Learning
• Predictive Analytics
• Statistical Modelling
• Data Mining
• Big Data Analytics
• Exploratory Data Analysis
• Feature Engineering
• Feature Selection
• Model Development
• Model Validation
• Model Optimisation
• Supervised Learning
• Unsupervised Learning
• Classification
• Regression
• Clustering
• Anomaly Detection
• Data Visualisation
• Statistical Analysis

Programming and Technical Requirements

Strong hands-on experience with one or more of the following is required:

Python, R and SQL

Candidates should also have practical knowledge relevant to data processing and transformation, large-scale datasets, data pipelines, cloud data platforms, machine-learning platforms and data-visualisation tools.

The employer is looking for practical Data Science experience rather than someone whose background consists only of reporting, business intelligence or basic data analysis.

Minimum Qualifications

Applicants need a relevant tertiary qualification.

Suitable fields include:

• Data Science
• Computer Science
• Information Technology
• Statistics
• Mathematics
• Applied Mathematics
• Engineering
• Information Systems
• Actuarial Science
• Another relevant quantitative or technology discipline

A relevant Diploma, Degree, Honours or Master’s qualification may be considered according to the requirements of the position.

Advantageous Certifications

Data Science and Machine Learning certifications are highly advantageous.

Examples identified by the employer include:

• Certified Data Scientist
• Microsoft Certified: Azure Data Scientist Associate
• SAS Certified Data Scientist
• IBM Data Science Professional Certification
• Google Professional Data Engineer
• Other recognised Data Science or Machine Learning certifications

Applicants who hold relevant certifications should include them with their applications where requested.

Experience Required

Candidates should be able to demonstrate genuine practical Data Science experience.

Relevant experience includes:

• Machine Learning
• Data Mining
• Big Data Analytics
• Predictive Analytics
• Statistical Modelling
• Python, R and/or SQL
• Data preparation and transformation
• Predictive-model development
• Machine-learning model validation
• Model optimisation
• Complex data analysis
• Converting analytical findings into business insights

Experience working on enterprise-scale data and analytics projects will be particularly advantageous.

Make Your Data Science Projects Clear on Your CV

Applicants should clearly explain their previous Data Science projects rather than simply listing technologies.

Where possible, your CV should identify the project or organisation, project duration, your role, technologies used, Data Science or Machine Learning methods applied, your specific responsibilities and the business outcome achieved.

This is especially important because the employer is looking for genuine hands-on Data Science experience.

Working With Other Teams

The Data Scientist will collaborate with professionals including Data Engineers, Business Analysts, Software Developers and business stakeholders.

The successful candidate should therefore be capable of explaining technically complex analytical findings in language that both technical and non-technical stakeholders can understand.

About Itonga Resourcing

Itonga Resourcing is a recruitment and consulting business specialising in areas including technology, IT, finance, engineering and legal recruitment.

For this vacancy, Itonga Resourcing is recruiting an experienced Data Scientist for one of its clients.

How to Apply

Candidates who meet the requirements can submit an application through the original PNet vacancy.

Before applying, make sure your CV clearly highlights your Data Science projects, Machine Learning experience, Python/R/SQL abilities, qualifications, relevant certifications and experience developing and validating predictive models.

Do not rely on a generic list of technical skills. Where possible, explain how you used those technologies to solve real problems and what results your work produced.

Important: JobMarketSA is an independent job-information website and is not Itonga Resourcing, PNet or the hiring organisation. Applicants should verify the vacancy and application requirements before submitting personal information.