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Operations Data Analyst, Expert

Cynet Systems
9 days ago
Contract
On-site
Oakland, California, United States
$77.14 - $82.14 USD hourly

Job Overview:

Pay Range: $77.14hr - $82.14hr

Requirement/Must Have:

  • Bachelor's degree in data science, computer science, engineering or equivalent experience.
  • 5+ years of related experience or equivalent.
  • Experience with programming and scripting languages, such as Python and SQL.
  • Experience with data warehousing, data quality, and ETL techniques.
  • Experience with data processing tools such as Excel, SharePoint, and Microsoft Lists.
  • Experience with financial and techno-economic modeling.

Responsibilities:

  • Identify opportunities to develop criteria and methodologies for incorporating flexible load resources into planning scenarios by working with planners to identify areas with overloads, reliability issues, and operational risks.
  • Connect with experts to understand available data sources and develop strategies that support the efficient management and application of that data to inform key decision-making.
  • Support the development of executive and board-level materials by synthesizing analytical findings, insights, and recommendations for key stakeholders and decision makers.
  • Support regulatory strategy, proceedings, stakeholder engagement, and DER valuation discussions with regulatory bodies and other stakeholders.
  • Leverage research and analysis to provide insights to planning and operations professionals on cost-effective ways to use flexible load resources to solve grid constraints.
  • Design and execute field studies and planning analyses to validate the firmness, duration, and magnitude of load relief, rate impacts, and financial outcomes delivered by DERs.
  • Develop an inventory of technical requirements to inform future load management program design and regulatory filings aligned with the organization's strategy.
  • Support the development, enhancement, and application of analytical tools, including complex techno-economic modeling, forecasting, data analysis, and program evaluation.
  • Gather, evaluate, and manage market, financial, regulatory, and other relevant industry data to support DER valuation and cost-effectiveness analyses.
  • Develop dashboards, visualizations, and executive-ready materials that translate complex technical and financial analyses into actionable recommendations.
  • Serve as a liaison between the LMS&P and Transmission and Distribution planning teams to integrate learnings into planning, procurement, and business processes.
  • Conduct benchmarking studies and use relevant industry data to support program and strategy development.
  • Collaborate with valuation and strategy leads to develop and apply DER valuation methodologies, including project planning and tool deployment.
  • Coordinate with internal teams, external vendors, aggregators, and industry partners to evaluate flexible load capabilities and implementation pathways.
  • Partner with program and customer-facing teams to ensure flexible load solutions are technically viable, cost-effective, and scalable.

Nice to Have:

  • Degree or advanced coursework in data science, engineering, economics, energy systems, or a related field.
  • Master's degree in business administration, engineering, or another advanced degree.
  • Experience with grid modeling, power flow, or planning tools such as CYMDIST, PSLF, Aspen, or similar applications.
  • Experience with business intelligence platforms, such as Power BI.
  • Experience in transmission or distribution system planning and operations.
  • Knowledge of DER integration, communications protocols, and grid impacts, including IEEE 2030.5, CSIP 2.1, OpenADR, aggregator APIs, and telecommunications.
  • Experience with DER valuation frameworks, financial modeling, and methodologies such as the Avoided Cost Calculator and Non-Wires Alternatives.
  • Demonstrated experience in project, product, or program management in the context of utility operations or IT systems.
  • Familiarity with utility regulations, regulatory processes, and policy context.

Skills:

  • Analytical proficiency.
  • Model building.
  • Python.
  • SQL.
  • ETL techniques.
  • Data warehousing.
  • Techno-economic modeling.
  • Power systems analysis.
  • Excel.
  • SharePoint.
  • Power BI.
  • Strong verbal and written communication skills.
  • Project management.
  • Stakeholder management.

Qualification And Education:

  • Organized and motivated with a track record of building consensus within matrixed teams.
  • Ability to navigate ambiguity and independently move concepts from strategy to execution.
  • High attention to detail and strong organizational skills.
  • Action-oriented self-starter mindset.