Principal Data Scientist

Responsibilities

Kforce has a client that is seeking a Principal Data Scientist in Juno Beach, FL. Overview: This role supports critical decision-making for Energy Management (EMT), Power Marketing (PMI), and System Operations (Sysops FPL). This position will engage in end-to-end model development-from conception through production deployment, including advanced feature engineering, weather data integration via APIs, model optimization, and performance monitoring. The ideal candidate will design production-ready forecasting solutions integrated with internal systems, AWS cloud infrastructure, implementing robust error handling, alerting mechanisms, and recovery procedures. The successful candidate should possess deep expertise in time-series forecasting, machine learning operations, and building scalable data pipelines. They must demonstrate the ability to transform complex datasets into actionable forecasts that drive real-time operational decisions in the energy sector. We are looking for someone who has a passion for solving challenging forecasting problems and can deliver production-grade solutions in a dynamic operational environment with stringent accuracy requirements and time-sensitive obligations. Responsibilities: Model Development & Production:

• Lead end-to-end forecasting model development for Load, Solar, and Wind from conception through production deployment
• Build automated retraining and evaluation frameworks with monitoring dashboards
  
  

Data & Infrastructure:

• Develop data connectors for weather APIs and data warehouse systems
• Design scalable pipelines for real-time and batch forecasting operations
• Create interactive dashboards (Streamlit) and present insights to stakeholders
  
  

Requirements

• Python Expertise: Advanced proficiency in Python with extensive experience in data science libraries (pandas, numpy, scikit-learn, statsmodels)
• Time-Series Forecasting: Proven track record developing and deploying production forecasting models (ARIMA, SARIMAX, gradient boosting methods)
• Production Deployment: Demonstrated experience taking models from research/development through production deployment with proper versioning, monitoring, and maintenance
• API Integration: Experience consuming and integrating weather APIs and external data sources into forecasting pipelines, with a strong background in data engineering
• Cloud & Infrastructure: Working knowledge of AWS services (EC2, S3, Lambda, SageMaker) and Infrastructure-as-Code practices
• Database Management: Proficiency with SQL databases and experience with large-scale data queries and optimization
• Dashboard Development: Experience building interactive dashboards using Streamlit, Plotly, or similar frameworks for stakeholder communication
  
  

Technical Competencies

• Feature engineering with weather variables and domain-specific signals
• Model evaluation metrics (MAE, RMSE, MAPE)
• Automated data pipelines and version control (Git)
  
  

Key Expectations

• Understands business priorities and takes ownership of the complete model lifecycle from development to production deployment
• Demonstrates strong communication and collaboration skills working with trading, operations, and engineering teams
• Able to work effectively within Agile frameworks and actively participate in scrum ceremonies
• Able to deliver cost-effective, high-quality forecasting solutions that meet operational deadlines and accuracy standards
  
  

Preferred Skills & Experience:

• Advanced feature engineering, uncertainty quantification, and probabilistic forecasting methods
• Energy markets and renewable generation forecasting domain expertise
• Agile project management (Jira, Confluence)
  
  

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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