Graduate Data Scientist

Teraco

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Specific city not spe…

Specific city not specified

Gauteng, ZA

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Posted Date:

12 May 2026

Closing Date:

31 May 2026

Tech

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Entry Level

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1 Programme Overview

eraco is looking for a motivated Data Scientist Graduate to join its experienced team in Gauteng. This opportunity is ideal for a driven and analytically minded graduate who is ready to work across Data Engineering, Artificial Intelligence, and Business Intelligence functions.

This 1–2 year contract is designed to provide real-world exposure to building data pipelines, deploying AI models, and delivering actionable business insights — all within a professional and collaborative environment that values continuous learning and innovation.

1 Programme Overview

2 Minimum Requirements

Applicants must have:

Degree in Data Science, Statistics, Computer Science or a related field
Experience with data analysis and machine learning using Python, R or similar tools
Experience with database querying using SQL
Experience with data engineering concepts
Experience with machine learning concepts and algorithms
Problem-solving mindset and strong attention to detail
Excellent communication and ability to simplify complex concepts

NB: Python proficiency is strongly preferred — candidates with hands-on Python coding experience will be prioritised in the shortlisting process.

2 Minimum Requirements

Applicants must have:

Degree in Data Science, Statistics, Computer Science or a related field
Experience with data analysis and machine learning using Python, R or similar tools
Experience with database querying using SQL
Experience with data engineering concepts
Experience with machine learning concepts and algorithms
Problem-solving mindset and strong attention to detail
Excellent communication and ability to simplify complex concepts

NB: Python proficiency is strongly preferred — candidates with hands-on Python coding experience will be prioritised in the shortlisting process.

2 Minimum Requirements

Applicants must have:

Degree in Data Science, Statistics, Computer Science or a related field
Experience with data analysis and machine learning using Python, R or similar tools
Experience with database querying using SQL
Experience with data engineering concepts
Experience with machine learning concepts and algorithms
Problem-solving mindset and strong attention to detail
Excellent communication and ability to simplify complex concepts

NB: Python proficiency is strongly preferred — candidates with hands-on Python coding experience will be prioritised in the shortlisting process.

2 Minimum Requirements

Applicants must have:

Degree in Data Science, Statistics, Computer Science or a related field
Experience with data analysis and machine learning using Python, R or similar tools
Experience with database querying using SQL
Experience with data engineering concepts
Experience with machine learning concepts and algorithms
Problem-solving mindset and strong attention to detail
Excellent communication and ability to simplify complex concepts

NB: Python proficiency is strongly preferred — candidates with hands-on Python coding experience will be prioritised in the shortlisting process.

3 Key Responsibilities

Successful applicants will be responsible for:

Data Engineering:

Designing and building scalable data pipelines
Incorporating best practices for managing big data — high volume, high velocity and high variety

Artificial Intelligence:

Building and deploying AI models in production environments
Implementing MLOps best practices across the full model lifecycle — data preparation, training, feature selection, evaluation, deployment, monitoring and maintenance

Business Intelligence:

Delivering actionable insights from complex data sets
Building insightful data visualisations to communicate findings clearly and effectively to stakeholders

NB: This role spans three disciplines — Data Engineering, AI and Business Intelligence — candidates must demonstrate competence or strong interest across all three areas.

3 Key Responsibilities

Successful applicants will be responsible for:

Data Engineering:

Designing and building scalable data pipelines
Incorporating best practices for managing big data — high volume, high velocity and high variety

Artificial Intelligence:

Building and deploying AI models in production environments
Implementing MLOps best practices across the full model lifecycle — data preparation, training, feature selection, evaluation, deployment, monitoring and maintenance

Business Intelligence:

Delivering actionable insights from complex data sets
Building insightful data visualisations to communicate findings clearly and effectively to stakeholders

NB: This role spans three disciplines — Data Engineering, AI and Business Intelligence — candidates must demonstrate competence or strong interest across all three areas.

3 Key Responsibilities

Successful applicants will be responsible for:

Data Engineering:

Designing and building scalable data pipelines
Incorporating best practices for managing big data — high volume, high velocity and high variety

Artificial Intelligence:

Building and deploying AI models in production environments
Implementing MLOps best practices across the full model lifecycle — data preparation, training, feature selection, evaluation, deployment, monitoring and maintenance

Business Intelligence:

Delivering actionable insights from complex data sets
Building insightful data visualisations to communicate findings clearly and effectively to stakeholders

NB: This role spans three disciplines — Data Engineering, AI and Business Intelligence — candidates must demonstrate competence or strong interest across all three areas.

3 Key Responsibilities

Successful applicants will be responsible for:

Data Engineering:

Designing and building scalable data pipelines
Incorporating best practices for managing big data — high volume, high velocity and high variety

Artificial Intelligence:

Building and deploying AI models in production environments
Implementing MLOps best practices across the full model lifecycle — data preparation, training, feature selection, evaluation, deployment, monitoring and maintenance

Business Intelligence:

Delivering actionable insights from complex data sets
Building insightful data visualisations to communicate findings clearly and effectively to stakeholders

NB: This role spans three disciplines — Data Engineering, AI and Business Intelligence — candidates must demonstrate competence or strong interest across all three areas.

4 What You Will Gain

Employees will benefit from:

1–2 years of structured hands-on experience across Data Engineering, AI and Business Intelligence
Real-world exposure to big data management, MLOps and data visualisation
Market-related remuneration for the duration of the contract
Mentorship and professional development in a data-driven environment
A strong and highly marketable portfolio of data science skills for your career

Tip: Experience across Python, SQL, MLOps and data visualisation tools gained in this role will make you one of the most competitive data science candidates in the South African job market!

4 What You Will Gain

Employees will benefit from:

1–2 years of structured hands-on experience across Data Engineering, AI and Business Intelligence
Real-world exposure to big data management, MLOps and data visualisation
Market-related remuneration for the duration of the contract
Mentorship and professional development in a data-driven environment
A strong and highly marketable portfolio of data science skills for your career

Tip: Experience across Python, SQL, MLOps and data visualisation tools gained in this role will make you one of the most competitive data science candidates in the South African job market!

4 What You Will Gain

Employees will benefit from:

1–2 years of structured hands-on experience across Data Engineering, AI and Business Intelligence
Real-world exposure to big data management, MLOps and data visualisation
Market-related remuneration for the duration of the contract
Mentorship and professional development in a data-driven environment
A strong and highly marketable portfolio of data science skills for your career

Tip: Experience across Python, SQL, MLOps and data visualisation tools gained in this role will make you one of the most competitive data science candidates in the South African job market!

4 What You Will Gain

Employees will benefit from:

1–2 years of structured hands-on experience across Data Engineering, AI and Business Intelligence
Real-world exposure to big data management, MLOps and data visualisation
Market-related remuneration for the duration of the contract
Mentorship and professional development in a data-driven environment
A strong and highly marketable portfolio of data science skills for your career

Tip: Experience across Python, SQL, MLOps and data visualisation tools gained in this role will make you one of the most competitive data science candidates in the South African job market!

5 Application Process

How To Apply:

Apply via the official recruitment portal
Use Reference Number: Grad_DSJB1
Submit your CV and all certified supporting documents including academic transcripts
Click the Apply Button — you will be redirected to the official application page

Tip: No closing date is specified — but make sure you apply before the end of this month 31 May 2026 to avoid missing out!

5 Application Process

How To Apply:

Apply via the official recruitment portal
Use Reference Number: Grad_DSJB1
Submit your CV and all certified supporting documents including academic transcripts
Click the Apply Button — you will be redirected to the official application page

Tip: No closing date is specified — but make sure you apply before the end of this month 31 May 2026 to avoid missing out!

5 Application Process

How To Apply:

Apply via the official recruitment portal
Use Reference Number: Grad_DSJB1
Submit your CV and all certified supporting documents including academic transcripts
Click the Apply Button — you will be redirected to the official application page

Tip: No closing date is specified — but make sure you apply before the end of this month 31 May 2026 to avoid missing out!

5 Application Process

How To Apply:

Apply via the official recruitment portal
Use Reference Number: Grad_DSJB1
Submit your CV and all certified supporting documents including academic transcripts
Click the Apply Button — you will be redirected to the official application page

Tip: No closing date is specified — but make sure you apply before the end of this month 31 May 2026 to avoid missing out!

6 Disclaimer

Spanisam lists jobs in good faith as an information platform only. We are not responsible for hiring decisions made by the employer. Always verify through official channels.

6 Disclaimer

Spanisam lists jobs in good faith as an information platform only. We are not responsible for hiring decisions made by the employer. Always verify through official channels.

6 Disclaimer

Spanisam lists jobs in good faith as an information platform only. We are not responsible for hiring decisions made by the employer. Always verify through official channels.

6 Disclaimer

Spanisam lists jobs in good faith as an information platform only. We are not responsible for hiring decisions made by the employer. Always verify through official channels.

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Spanisam is 100% free for job seekers, and no fees are allowed at any stage of the application process. Any request for payment should be reported to us immediately.

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The data on this page gets updated

Hello Mzansi • May 13, 2026 • 06:39:37

Report An Issue

The data on this page gets updated

Hello Mzansi • May 13, 2026 • 06:39:37