Data Scientist

SIDRAM TECHNOLOGIES; Juno Beach (FL); On-site; USD 120,000 - 160,000; Full time

Job summary

A leading technology firm in Juno Beach, FL, seeks a Principal Data Scientist to lead the development of advanced forecasting models for Load and Renewable Generation. The successful candidate will engage in end-to-end model development with a focus on time-series forecasting and model deployment on AWS. This is an onsite position with expectations for collaboration within Agile frameworks. Ideal qualifications include expertise in Python, production deployment of forecasting models, and experience with weather APIs. A passion for solving challenging forecasting problems is essential.

Qualifications

• Deep expertise in time-series forecasting and machine learning operations.
• Proven track record developing and deploying production forecasting models.
• Experience with weather data integration and data engineering.

Responsibilities

• Lead the model development from conception to production deployment.
• Build automated retraining and evaluation frameworks with dashboards.

Skills

Python expertise

Time-series forecasting

Production deployment experience

API integration

AWS services knowledge

SQL database management

Dashboard development

Tools

pandas

numpy

scikit-learn

statsmodels

Streamlit

Plotly

Git

Job description

Location: Onsite – 5 Days / Week – Juno Beach Florida

Position: Principal Data Scientist - Load & Renewable Generation Forecasting

Position Specific Description

The IT Forecasting team is seeking a Principal Data Scientist to lead the development and production deployment of advanced forecasting models for Load, Solar, and Wind generation across. 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 and 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.

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
• Works effectively within Agile frameworks and actively participates in scrum ceremonies
• Deliver cost‑effective, high‑quality forecasting solutions that meet operational deadlines and accuracy standards

Required Skills & Experience

• Python expertise 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

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)

Technical Competencies

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

Job Duties & Responsibilities

• 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

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