Key Responsibilities and Required Skills for Wind Analyst

🎯 Role Definition

A Wind Analyst is responsible for assessing wind resources, estimating energy yield and uncertainty, analyzing SCADA and met-mast/LiDAR data, and producing commercially actionable reports and recommendations that support wind farm development, financing, due diligence, construction and operations. This role requires hands-on experience with wind modeling tools (WRF, WAsP, WindPRO/OpenWind/WindFarmer), strong data science skills (Python, R, MATLAB, SQL), familiarity with SCADA and met measurement systems, and knowledge of industry standards (IEC 61400 series).

📈 Career Progression

Typical Career Path

Entry Point From:

Junior Meteorologist / Meteorological Technician
Renewable Energy Data Analyst or SCADA Analyst
Environmental / Wind Resource Intern with strong analytics background

Advancement To:

Senior Wind Analyst / Lead Wind Resource Engineer
Energy Yield Manager / Senior Resource Assessment Manager
Head of Wind Resource & Energy Forecasting
Project Development Manager / Asset Manager

Lateral Moves:

Wind Farm Performance Analyst
SCADA & Condition Monitoring Specialist
Site Assessment Consultant / Environmental Specialist

Core Responsibilities

Primary Functions

Lead comprehensive wind resource assessments for prospective and operational sites by integrating mesoscale modeling (WRF, MeteoModels) with microscale tools (WAsP, WindPRO, OpenWind), on-site met mast and remote sensing (LiDAR/SODAR) data, to produce robust mean wind speed maps and vertical shear profiles that inform turbine selection and layout decisions.
Prepare independent energy yield assessments (P50/P90) using industry-standard methodologies; quantify energy production, wake losses, array losses, electrical losses, and curtailment impacts and deliver bankable energy reports for financiers, developers and asset managers.
Process, clean and QA/QC high-frequency SCADA data and met mast/LiDAR datasets; identify and correct corrupted records, sensor drift, icing downtime, yaw and met bias, and apply appropriate filtering and statistical correction techniques to produce reliable datasets for modeling and forecasting.
Perform statistical and uncertainty analyses that include KDT (Kernel Density), Monte Carlo simulations, bootstrap resampling and sensitivity studies to quantify measurement, model and site uncertainty; clearly communicate P-values, confidence intervals and risk drivers in reports.
Develop and run mesoscale-to-microscale workflows (e.g., WRF → WindPRO/WindFarmer) including terrain, roughness, thermal stratification and coastal effects; validate model outputs against observations and iteratively refine model parameterization for site-specific accuracy.
Conduct wake modeling and array optimization studies (Fuga, FarmFlow, WindFarmer), evaluate multiple wake loss models and mitigation options, and provide optimized turbine siting and layout recommendations that balance energy yield, cost and environmental constraints.
Lead measurement campaign design and implementation for met mast and remote sensing deployments (LiDAR/SODAR): define sensor type, mast height, measurement duration, siting, calibration procedures and data telemetry requirements to meet IEC 61400-12 and bankable study standards.
Produce detailed project deliverables — energy yield reports, bankable forecast documents, sensitivity matrices, LCOE impact statements and GIS maps — tailored to developers, investors, utilities and permitting authorities.
Integrate resource assessment with electrical system studies and grid connection analyses to quantify curtailment risk, capacity factor, availability and grid compliance considerations across project lifetime.
Manage and ingest large time-series datasets into databases and data pipelines (SQL, time-series DBs), implement data versioning and reproducible analysis workflows to support long-term asset monitoring and retrospective performance attribution.
Collaborate with civil, electrical and procurement teams to ensure that wind resource insights drive turbine selection, foundation and micro-siting decisions, road access planning and cable routing to reduce wakes, turbulence and construction risk.
Serve as the technical lead during due diligence and third-party review processes: prepare technical memos, respond to lender queries, and present methodological assumptions and uncertainty quantification to investors and insurers.
Conduct post-construction performance validation and annual energy assessments by comparing measured SCADA output to pre-construction yield estimates, calculating availability, losses, and performing root-cause analysis for underperformance.
Maintain strong familiarity with IEC 61400 standards (particularly IEC 61400-12 for power performance testing) and ensure measurement and reporting practices are compliant and defensible in regulatory and financing contexts.
Implement advanced analytics for predictive maintenance and performance optimization by deriving performance indicators from SCADA and meteorological data, developing thresholds for alarms and recommending O&M strategies that maximize energy capture.
Create automated modeling and reporting scripts (Python, MATLAB, R) and CI/CD data workflows to reduce turnaround time for energy assessments, standardize methodologies and maintain reproducibility across projects.
Lead sensitivity and scenario analyses to quantify impacts of hub height choices, turbine power curves, availability assumptions, and climate-adjusted wind regimes on lifetime energy production and revenue.
Supervise and coordinate with field technicians and vendors during measurement installations, calibration events, and site inspections to ensure data integrity, health and safety compliance, and timely data delivery.
Build and maintain geospatial and site constraint databases using ArcGIS/QGIS for siting assessments, turbine exclusion zones, environmental buffers and terrain analysis that directly feed micrositing models.
Present technical findings and commercial implications to internal stakeholders and external clients using clear visualizations, executive summaries and technical appendices tailored to both technical and non-technical audiences.
Drive continuous improvement by benchmarking models against industry best practices, adopting new modeling techniques (e.g., machine learning for wake loss estimation), and contributing to internal knowledge bases and standard operating procedures.
Support multi-disciplinary project teams across development, construction and operations phases by translating wind data insights into actionable project requirements, risk matrices and contingency plans.

Secondary Functions

Provide ad-hoc analytics and exploratory data analysis to support commercial bids, feasibility studies and in-house R&D on farm performance and power curve degradation.
Contribute to the organization’s data strategy by helping define data standards, metadata practices and the roadmap for SCADA/LiDAR data storage and access.
Collaborate with business units to translate resource assessment needs into engineering and procurement requirements (e.g., turbine selection, hub height trade-offs).
Participate in project sprint planning, agile ceremonies and cross-functional reviews to align wind-resource deliverables with project milestones and investor timelines.
Mentor junior analysts and interns on measurement campaigns, QC procedures, modeling workflows and communication of energy risk to stakeholders.
Evaluate and recommend instrumentation, software licenses and third-party consulting services required for measurement, modeling and performance monitoring.
Assist with regulatory submissions, permitting support and environmental assessments by providing wind and noise contour maps, and turbine placement justification.
Support sales and proposal teams by estimating scope, schedule and resourcing for wind resource assessments and for pre-bid technical clarifications.

Required Skills & Competencies

Hard Skills (Technical)

Wind resource assessment and energy yield modeling (P50/P90) — demonstrated experience producing bankable energy reports.
Mesoscale and microscale modeling: WRF, WAsP, WindPRO, OpenWind, WindFarmer or equivalent.
SCADA data analysis: time-series processing, filtering, availability calculation and performance attribution.
Remote sensing and met-mast data processing: LiDAR/SODAR analysis, mast calibration, met sensor QA/QC.
Statistical and uncertainty analysis: Monte Carlo, bootstrap, Bayesian methods, sensitivity analysis.
Programming and automation: Python (pandas, xarray, numpy), R or MATLAB for data cleaning, modeling and reporting.
Database and data pipelines: SQL, time-series databases, ETL practices, version control (Git).
GIS and spatial analysis: ArcGIS / QGIS for terrain analysis, mapping and micrositing inputs.
Wake and array loss modeling: Fuga, FarmFlow, FLORIS or equivalent tools.
Familiarity with industry standards and regulations: IEC 61400 series, power performance testing protocols.
CFD basics (OpenFOAM or commercial CFD tools) for complex terrain or layout-specific turbulence studies.
Proficiency in Microsoft Excel (advanced formulas, pivot tables) and data visualization tools (Matplotlib, Plotly, Power BI, Tableau).
Knowledge of electrical losses, curtailment modeling and LCOE impacts related to resource assessment.
Experience with cloud computing and containerized workflows (AWS/Azure, Docker) for scalable modeling.
Report writing and technical documentation skills suitable for investors, lenders and permitting authorities.

Soft Skills

Strong verbal and written communication with ability to present complex technical findings to both technical and non-technical stakeholders.
Critical thinking and problem-solving with attention to detail and a structured approach to uncertainty and data quality issues.
Project management skills: task prioritization, timeline management, stakeholder coordination and delivery under tight deadlines.
Teamwork and collaboration across multi-disciplinary teams (development, construction, operations, finance).
Client-facing professionalism: ability to respond to RFPs, defend methodology in due diligence and build trust with external parties.
Adaptability and continuous learning mindset to stay current with evolving modeling tools, measurement technologies and industry standards.
Mentoring and coaching capabilities to upskill junior staff and build internal analytical capability.
Commercial awareness: understand how wind resource findings impact project economics, contracts and financing.

Education & Experience

Educational Background

Minimum Education:

Bachelor’s degree in Meteorology, Atmospheric Science, Mechanical/Electrical Engineering, Renewable Energy, Applied Mathematics, Physics, or a closely related quantitative field.

Preferred Education:

Master’s degree (or higher) in Wind Energy, Atmospheric Science, Renewable Energy Systems, or Engineering with specialization in fluids/atmospheric modeling.

Relevant Fields of Study:

Meteorology / Atmospheric Sciences
Renewable Energy / Wind Energy Engineering
Mechanical / Civil / Electrical Engineering (with wind/atmospheric focus)
Applied Mathematics / Statistics / Data Science

Experience Requirements

Typical Experience Range: 2–7 years of direct wind resource assessment, SCADA analytics, or wind farm performance analysis.

Preferred:

5+ years experience working on wind farm development, asset management or third-party bankable assessments with demonstrable delivery of P50/P90 reports.
Practical field experience with met masts, LiDAR/SODAR deployments and instrumentation calibration.
Experience working with lenders, insurers or clients on technical due diligence is highly desirable.