Key Responsibilities and Required Skills for Weather Program Analyst

🎯 Role Definition

As a Weather Program Analyst you will bridge atmospheric science, data analytics, and program execution to deliver reliable, actionable weather information to internal and external stakeholders. You will design and maintain forecasting workflows, evaluate and improve models and observation systems, translate meteorological datasets into decision-ready products, and manage program requirements, timelines, and quality assurance. The role requires applied meteorology experience, strong data skills (Python/R/SQL), familiarity with NWP and remote sensing, and proven stakeholder engagement and program management abilities.

📈 Career Progression

Typical Career Path

Entry Point From:

Operational Meteorologist / Forecast Technician
Atmospheric Science or Meteorology Data Analyst
Climate or Environmental Data Specialist

Advancement To:

Senior Weather Program Analyst / Lead Meteorological Analyst
Forecast Operations Manager or Chief of Forecast Services
Data Science Lead for Weather Programs / NWP Developer
Program Manager, Weather & Climate Services

Lateral Moves:

Climate Services Analyst
NWP (Numerical Weather Prediction) Developer
Geospatial Analyst / GIS Specialist
Decision Support Product Manager

Core Responsibilities

Primary Functions

Design, implement, and manage weather program workflows that combine observations, remote sensing (radar, satellite), and numerical weather prediction (NWP) output into operational forecast products and decision-support tools for internal and external customers.
Conduct end-to-end meteorological analyses—bias correction, ensemble aggregation, downscaling, and post-processing—to improve deterministic and probabilistic forecasts for aviation, energy, emergency management, and transportation sectors.
Lead verification and performance monitoring of forecast systems and models using rigorous statistical techniques; produce verification reports, scorecards, and trends to guide model tuning and operational improvements.
Maintain and optimize data ingestion pipelines from multiple sources (surface networks, profilers, radar, satellite, reanalysis) and implement automated quality control (QC) and flagging to ensure data integrity and traceability.
Develop, validate, and operationalize custom algorithms and scripts (Python, R, MATLAB) for specialized meteorological products such as precipitation type, icing, turbulence, and convective initiation probabilities.
Coordinate with NWP model teams and vendors to evaluate model upgrades, assimilation changes, and ensemble configurations; plan and conduct model change impact assessments and transition strategies.
Build and maintain geospatial and temporal climatologies, hazard databases, and threshold-based triggers used for alerting, service-level agreements, and resource allocation during weather events.
Translate complex meteorological output into crisp, actionable briefings, graphical dashboards, and automated alerts tailored to stakeholder needs (executive summaries, technical appendices, and operational checklists).
Drive requirements gathering and user acceptance testing (UAT) for new forecasting tools and program features; create test plans, acceptance criteria, and runbooks to ensure reliability in operations.
Produce technical documentation, standard operating procedures, and knowledge transfer materials for forecasting operations, QC processes, and data provenance to support 24/7 operations and cross-training.
Design and implement forecast ensemble and probabilistic solutions, including calibration, reliability diagrams, and decision-focused probabilistic metrics, to support risk-based decision making.
Conduct sensitivity and impact studies to quantify the value of additional observations (e.g., targeted observations, new radar sites) and advise on observing system deployment and cost-benefit tradeoffs.
Integrate machine learning and statistical post-processing methods for bias reduction, nowcasting enhancement, and automated pattern recognition (e.g., severe convection signatures, snow-rain transition).
Collaborate with software engineers and cloud engineers to productionize models and services (containerization, CI/CD, cloud deployment) while ensuring reproducibility and operational resilience.
Provide operational forecasting support during high-impact weather events, including producing situational awareness products, participating in incident management calls, and adjusting program priorities in real time.
Manage vendor and partner relationships for model licensing, data subscriptions, and third-party tools; negotiate SLAs and ensure data delivery meets program uptime and latency requirements.
Conduct training sessions and workshops for forecasters, partners, and stakeholders on tool use, forecast interpretation, and uncertainty communication to improve adoption and decision quality.
Implement and maintain metadata standards, data catalogs, and APIs that enable discoverability and programmatic access to weather datasets for downstream applications and partners.
Monitor relevant regulatory and science developments (e.g., NWP advances, new remote sensing platforms) and synthesize emerging capabilities into short- and long-term program roadmaps.
Lead cross-functional project teams to deliver new forecast services or feature releases, tracking milestones, budgets, dependencies, and risk mitigation strategies to meet stakeholder expectations.
Perform retrospective analysis and lessons learned after significant events to refine SOPs, update models, and enhance communication protocols, ensuring continuous program improvement.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Provide subject-matter expertise to marketing and product teams to ensure weather messaging is scientifically accurate and user-focused.
Assist in preparing grant proposals, technical appendices, and budget justifications for observational or modeling enhancements.
Participate in interoperability and standards working groups to align program outputs with partner formats (WMO, AWIPS, OGC, JSON-based APIs).
Mentor junior analysts and interns on best practices in forecast verification, data QC, and reproducible research workflows.

Required Skills & Competencies

Hard Skills (Technical)

In-depth knowledge of atmospheric science, synoptic meteorology, mesoscale processes, and climatology relevant to operational forecasting.
Hands-on experience with numerical weather prediction (NWP) systems, ensemble forecasting, model output post-processing and verification.
Strong programming and scripting skills: Python (xarray, pandas, NumPy, SciPy), R (tidyverse), and experience with scientific libraries.
Data engineering fundamentals: SQL, data pipelines, ETL processes, and experience working with large time-series and gridded datasets.
Remote sensing and radar product expertise: satellite imagery interpretation, radar reflectivity and velocity, precipitation estimation, and derived products.
Geospatial analysis skills: GIS, netCDF/GRIB data handling, coordinate transformations, and visualization of spatial datasets.
Statistical analysis and machine learning methods for calibration, probabilistic forecasting, and anomaly detection (scikit-learn, TensorFlow/PyTorch experience a plus).
Experience with data visualization and dashboarding tools (Matplotlib, Cartopy, Plotly, D3, Tableau, Power BI) to create stakeholder-ready products.
Familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker), and CI/CD practices for operational deployment.
Knowledge of quality control procedures, metadata standards, APIs (REST), and data cataloging for operational weather systems.
Proficiency in UNIX/Linux environments, version control (Git), and automation/orchestration tools for production workflows.
Experience performing model change impact assessments, value-of-information analyses, and observing system simulation experiments is desirable.

Soft Skills

Clear, concise communication skills for technical and non-technical audiences; experience writing technical reports and stakeholder briefings.
Strong stakeholder management and customer-focused mindset; ability to translate technical outputs into decision-ready guidance.
Analytical problem-solving and critical thinking with attention to detail and a bias for data-driven decisions.
Project and program management skills: organizing cross-functional teams, prioritizing tasks, and delivering on schedule.
Collaborative team player who can mentor, teach, and integrate feedback across scientific and engineering disciplines.
Adaptability under pressure; comfortable supporting 24/7 operations and shifting priorities during high-impact weather.
Initiative and continuous learning orientation to keep pace with advances in meteorology, data science, and operational practices.
Ethical handling of sensitive data and adherence to data governance, security, and privacy practices.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Meteorology, Atmospheric Science, Climate Science, Earth Science, Physics, Applied Mathematics, Computer Science, or a closely related field.

Preferred Education:

Master's degree or PhD in Atmospheric Science, Meteorology, Applied Mathematics, Atmospheric Physics, Data Science with meteorological focus, or similar advanced technical degree.

Relevant Fields of Study:

Meteorology / Atmospheric Science
Climate Science / Environmental Science
Data Science / Statistics / Computer Science
Geosciences / Applied Mathematics

Experience Requirements

Typical Experience Range:

2–7 years of relevant experience in operational forecasting, meteorological analysis, or weather-related data programs.

Preferred:

5+ years of combined operational meteorology and analytical experience, including direct involvement with NWP, remote sensing, model verification, and productionizing forecast services. Experience in a 24/7 operational environment, stakeholder-facing roles, or domain-specific sectors (aviation, energy, emergency management) is a strong plus.