Senior Advisor Data Science

Eskom Holdings SOC Ltd; South Africa; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

Eskom Holdings SOC Ltd in Gauteng is seeking a Senior Advisor Data Science to lead the design and deployment of AI, ML, and DL solutions within the Market Operator division. The role focuses on leveraging advanced data analytics to improve business outcomes while deriving value for the business unit in Simmerpan, Germiston.

Required are a strong background in AI/ML/DL, data modelling, databases, and SAP MR1, with a minimum of five years in data science, analytics, and related domains.

Qualifications

• B Degree/BTech in Computer Science/Mathematics/Statistics/Physics/Engineering/Actuarial Science at NQF7 with 360 credits.
• Related 5 years’ experience in Data science and analytics including AI/ML/DL.

Responsibilities

• Architect, design, develop and deploy AI/ML/DL solutions.
• Build, maintain and improve analytic models, reporting solutions and decision systems.
• Innovate and design new machines to learn prototypes and solutions.
• Manage the data science portfolio and the advanced analytics roadmap.
• Research, upskill and stay abreast of new developments.

Skills

Audio/video processing

Neural network architecture

Problem solving

Analytical thinking

Creative thinking

Data analytics

Education

Bachelor/ BTech in CS/Math/Statistics/Physics/Engineering/Actuarial Science

Tools

SAP MR1

Job description

Industry: Electricity, Energy & Water Supply

Job category: Energy and Power Engineering

Contract: Permanent

Remuneration: Market Related

EE position: Yes

Introduction

Position: Snr Advisor Data ScienceTask Grade: G16Area of specialization: To design artificial intelligence (AI), machine learning (ML) and deep learning (DL) solutions for the division by leveraging advanced data analytics to improve business outcomes while deriving value for business.Department: Market OperatorBusiness Unit: Energy Market ServicesLocation: Simmerpan - Germiston, Gauteng

Skills and Competencies Required

Behavioural:

• Honesty
• Ethics

Leadership:

• Critical thinking
• Sound business and people management acumen
• Manage vision and purpose

Knowledge:

• System, Applications and Products (SAP) Material Requester (MR1)
• Understand and demonstrate agile development life cycles
• Data sciences specialist topics of artificial intelligence, machine learning and deep learning
• Databases and foundation models
• Various software extensions, principles and standards
• Data modelling and evaluation
• Signal processing techniques

Skill

• Audio and video processing
• Neural network architecture
• Mechanical thinking
• Think creatively and innovatively.
• Problem solving and decision-making
• Analytical, mathematical, and creative problem-solving

Key Responsibilities

• Architect, design, develop and deploy AI/ML/DL solutions.
• Build, maintain and improve analytic models, reporting solutions and decision systems.
• Innovate and design new machines to learn prototypes and solutions.
• Manage the data science portfolio and the advanced analytics roadmap.
• Research, upskill and stay abreast of new developments.

“If you have not been contacted within 28 days after the closing date of this advertisement, please accept that your application was unsuccessful.”

“NTCSA is committed to equality, employment equity, and diversity. In accordance with the employment equity plan of NTCSA and its employment equity goals and targets, preference may be given, but is not limited, to candidates from under-represented designated groups. NTCSA reserves the right not to make an appointment to the posts as advertised. Candidates with disabilities are encouraged to apply for positions.”

NTCSA is committed to providing a smoke-free environment for its employees and visitors at the workplace.

Qualification(s):

B Degree/BTech in Computer Science/Mathematics/Statistics/Physics/Engineering/Actuarial Science at

NQF7 with 360 credits

Experience

Related 5 years’ experience in Data science and analytics including artificial intelligence (AI), machine learning (ML), deep learning (DL)