Data Scientist - Integrated Power Analytics

Job Requisition ID

13106

Closing Date

8 October 2026

OME

BST: Business Building

Location

Sandton

Purpose of Job

Accountable for developing and applying advanced data science, statistical modelling, forecasting and pricing analytics to support Sasol’s Integrated Power portfolio, including generation, demand, market exposure, commercial risk, portfolio optimisation and value creation.

The role develops analytical models, forecasting methodologies, scenario tools and decision-support outputs to improve commercial decision-making across the power portfolio. ETRM enablement, SAWEM readiness support, energy management analytics, Power BI and Aveva PI are positioned as future-facing application areas or enabling toolsets where this capability may be applied; prior exposure to these areas would be advantageous.

The role serves as the specialist analytics interface between Integrated Power, trading, asset management, commercial, finance, digital and operational teams, converting complex generation, load, market, metering, contractual, pricing, financial and risk data into reliable insight, measurable value opportunities and defensible commercial decisions

Key Accountabilities

Advanced Analytics, Statistical Modelling and Decision Support

• Develop and maintain statistical models, analytical tools and scenario engines to support Integrated Power decision-making.
• Convert generation, demand, market, pricing, metering, contractual, financial and risk data into actionable commercial insight.
• Analyse portfolio positions, market exposure, imbalance risk and optimisation opportunities across Sasol’s contracted and future power portfolio.
• Develop dashboards, analytical outputs and management reports that support operational, commercial and executive decision-making.
• Identify value creation opportunities through improved forecasting, pricing insight, resource allocation and portfolio optimisation.

Forecasting, Pricing Analytics and Portfolio Optimisation

• Develop, test and improve load, generation, renewable supply, price and imbalance forecasting methodologies.
• Apply pricing analytics to assess market signals, tariff structures, bilateral pricing, imbalance exposure and commercial optimisation options.
• Support short-, medium- and long-term portfolio optimisation across internal generation, renewable PPAs, market purchases, customer commitments and future trading positions.
• Track forecast accuracy, model performance and variance drivers, and recommend improvements to data, assumptions and methodologies.
• Quantify commercial impacts of forecast error, curtailment, constraints, outages, price movements and imbalance positions.
• Support the optimal deployment of electrons by providing insight into when, where and how Sasol’s power resources should be contracted, allocated, dispatched or hedged.

ETRM Enablement, SAWEM Readiness and Market Analytics

Data Governance, Performance Measurement and Value Tracking

• Establish structured datasets, assumptions registers, model documentation and version control for key analytical outputs.
• Maintain data quality checks, exception reporting and governance over analytical inputs and outputs.
• Measure performance against forecasts, portfolio strategies, pricing assumptions, optimisation cases and realised commercial outcomes.
• Track value creation opportunities, benefits realisation and analytical recommendations implemented by the business.
• Support auditability, assurance and governance of models, data sources, assumptions and decision-support outputs.

Stakeholder Collaboration and Capability Building

• Work with trading, commercial, asset management, finance, digital, operations and external partners to translate business questions into analytical solutions.
• Build internal capability by documenting methodologies, training users and embedding repeatable analytical processes.
• Provide analytical input into business cases, investment decisions, contract evaluations and market-readiness activities.
• Communicate insights clearly to technical and non-technical stakeholders through dashboards, reports, presentations and decision papers.
• Reduce dependency on external advisors by developing sustainable internal analytics capability for Integrated Power.

Key Working Interfaces

• Integrated Power business building, asset management, supply chain, information management, commercial, trading and portfolio management teams.
• Finance, risk, legal, assurance and internal control functions requiring analytical input, commercial insight and governance over assumptions.
• Digital, data, ETRM, metering, forecasting, Aveva PI, Power BI, energy management and reporting teams responsible for data integration, model enablement and system implementation.
• Generators, IPPs, customers, service providers and external advisors where analytical inputs are required for portfolio, contract, market-readiness or energy management decisions.
• Market, system and network operators where relevant to future market participation, data requirements, settlements or commercial exposure analysis.

Knowledge and Capability Requirements

• Strong capability in data science, advanced analytics, statistical modelling, optimisation, forecasting and scenario analysis.
• Experience working with time-series, operational, market, financial or commercial datasets to support business decision-making.
• Ability to develop pricing analytics, forecast models, portfolio scenarios, dashboards and decision-support tools.
• Working knowledge of electricity, energy, commodity, trading, optimisation or similar commercial environments would be advantageous.
• Exposure to ETRM systems, electricity market platforms, SAWEM, Power BI, Aveva PI or energy-market reform would be advantageous.
• Exposure to energy management, energy efficiency, demand-side management, site energy performance or energy consumption analytics would be advantageous.
• Strong data governance discipline, including model documentation, assumption management, validation, auditability and version control.
• Ability to communicate complex analytical findings clearly to technical and non-technical stakeholders through reports, dashboards and decision papers.

Qualifications and Experience

• University Bachelor’s degree in Engineering, Data Science, Statistics, Mathematics, Econometrics, Computer Science, Economics, Finance, Business Analytics or a related quantitative discipline.
• 9 years of experience

Competencies

• Customer Centricity: Engages with internal customers and stakeholders to understand business requirements and provide analytical insight that supports informed commercial and operational decisions.
• Business Acumen: Applies understanding of the Integrated Power business, electricity markets, portfolio value drivers, pricing, forecasting and commercial risk to produce relevant decision-support outputs.
• Commercial Agility: Uses analytics, modelling and scenario assessment to support timely, evidence-based commercial decisions in a dynamic market environment.
• Technical and Analytical Excellence: Builds robust analytical models, forecasts, dashboards and optimisation tools, while ensuring assumptions, data quality and outputs are properly tested and governed.
• Delivery Excellence: Creates practical, reliable and repeatable analytical solutions that support delivery against business priorities, project milestones and value-creation objectives.
• Partnership: Works collaboratively across Integrated Power, trading, asset management, finance, digital, operations and external partners to convert complex data into actionable insight.
• Develop Self: Maintains and develops knowledge of data science, electricity markets, ETRM systems, SAWEM readiness, Power BI, Aveva PI and related analytical tools.
• Builds Talent: Shares methods, documents models, supports users and helps build sustainable internal analytics capability.
• Inspirational: Communicates analytical findings clearly and confidently to technical and non-technical stakeholders, enabling sound business decisions.
• Collaborative: Initiates collaboration, removes barriers to cross-functional working and engages inclusively across business, digital and operational teams.