Role Purpose

The Data Scientist will build the analytical capability of the Power Trading Function. The role connects trading operations, settlement data, trader decisions, market fundamentals, risk controls and management reporting into one consistent and auditable operating system.

This is not a pure research or model-development position. The successful candidate will work closely with traders and the Power Trading Manager to explain results, capture how decisions were made, identify repeatable patterns, improve operating discipline and turn practical AI tools into measurable improvements in trading management and daily operations.

Key Responsibilities

1. Trading Data Control and Settlement Assurance

• Own the analytical data layer for medium-to-long-term contracts, spot transactions, generation, market prices, settlements, invoices and non-trading adjustments across the portfolio.
• Define data standards, validation rules, reconciliation checks, source hierarchy and exception logs so that reports can be traced back to authoritative source documents.
• Investigate data breaks and settlement variances with traders, project teams and external service providers, and maintain a clear audit trail from source data to management output.
• Automate recurring data collection, cleaning, settlement reconciliation and reporting workflows while preserving review checkpoints and manual override governance.

2. Post-Trade Review and Performance Attribution

• Produce daily, weekly and monthly performance analysis covering revenue, achieved price, position, volume, benchmark variance and key market drivers.
• Decompose trading outcomes into controllable and non-controllable drivers, including position decisions, price execution, forecast error, curtailment, congestion, market design, mechanism settlement and other charges.
• Build consistent benchmarks and scenario comparisons to distinguish genuine trading value-add from market movements, asset conditions and settlement effects.
• Convert analysis into concise conclusions, management actions and follow-up owners rather than producing reports without operational closure.

3. Trader Behaviour and Process Intelligence

• Create a structured decision log linking market context, forecasts, positions, bid changes, trader rationale, approvals and realized outcomes.
• Analyse recurring decision patterns, process deviations, timing issues and execution errors to identify which behaviours improve or weaken portfolio performance.
• Turn effective trading practices and lessons learned into repeatable playbooks, review templates, operating procedures and training materials.
• Support fair and evidence-based performance discussions by separating decision quality, execution quality and outcome variability.

4. AI-Enabled Operations and Knowledge Management

• Identify and implement practical AI use cases for power trading operations, such as document extraction, policy and rule retrieval, settlement exception detection, report drafting, decision-log summarisation and trading knowledge search.
• Build governed AI-assisted workflows using appropriate methods with human review for material trading and reporting decisions.
• Establish evaluation criteria for accuracy, traceability, data confidentiality and business adoption; prevent unverified AI output from entering trading, settlement or management reporting processes.
• Work with corporate IT and external vendors on secure data access, interfaces, deployment and maintenance of analytical tools.

5. Risk, Compliance and Control Analytics

• Develop monitoring for position limits, price deviations, missed submission deadlines, unusual transactions, data-quality failures and other operational risk indicators.
• Support compliance reviews by maintaining evidence of trading decisions, approvals, changes and submissions, and by testing trading behaviour against applicable market rules and internal controls.
• Assist the Power Trading Manager and future Risk and Compliance function with stress testing, scenario analysis, counterparty performance review and control improvement.

6. Market, Vendor and Management Support

• Combine market fundamentals, policy changes, generation forecasts and price signals with portfolio data to support trading strategy and scenario analysis.
• Maintain objective scorecards for third-party trading and market-intelligence providers, including data quality, timeliness, forecast performance, execution quality, settlement outcomes and issue closure.
• Prepare clear dashboards, analytical briefs and presentation materials for management, translating complex market and trading information into decisions and actions.

Qualifications

Required

• Master's degree in Data Science, Statistics, Computer Science, Mathematics, Electrical Engineering, Energy Economics, Finance or a related quantitative discipline.
• At least 2 years of relevant experience in data analytics, quantitative analysis, AI product delivery, energy market operations, commodities, financial services or another data-intensive operating environment.
• Strong Python and SQL skills, advanced Excel capability and practical experience with business intelligence or visualisation tools.
• Demonstrated ability to clean and reconcile complex operational data, investigate exceptions, document assumptions and create repeatable analytical workflows.
• Practical experience applying AI or machine learning to real business workflows, with an understanding of model evaluation, human review, data privacy and output traceability.
• Strong written and verbal communication skills, including the ability to explain technical findings to traders, management and non-technical stakeholders.
• High attention to detail, ownership of deadlines and the judgement to escalate data, control or interpretation issues before they affect decisions.

Preferred

• Experience with China's electricity markets, renewable generation, power trading, settlement, forecasting, risk control or market-data platforms.
• Understanding of medium-to-long-term trading, spot markets, contract-for-difference or mechanism settlements, congestion, curtailment and ancillary services.
• Experience building decision logs, knowledge bases, AI copilots, anomaly detection or automated document-processing workflows.
• Experience working across business, trading, risk, compliance, IT and external vendors in a regulated environment serve as an added advantage.
• Professional working proficiency in both Chinese and English.