Job description

Duration: 12+ Months Job 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 client operations. 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: • 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 Experience: • 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 Skillset: • Feature engineering with weather variables and domain-specific signals • Model evaluation metrics (MAE, RMSE, MAPE) • Automated data pipelines and version control (Git) Education: • Bachelor's Degree in Data Science, Computer Science or related area. Additional Qualifications: • Advanced feature engineering, uncertainty quantification, and probabilistic forecasting methods • Energy markets and renewable generation forecasting domain expertise • Agile project management (Jira, Confluence) Shift Hours: 8:00AM -5:00 PM CST About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com . US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring. IND01 #LI-AS140

Requirements

Must-haves

Duration: 12+ Months
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
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
Feature engineering with weather variables and domain-specific signals
Model evaluation metrics (MAE, RMSE, MAPE)
Automated data pipelines and version control (Git)
Bachelor's Degree in Data Science, Computer Science or related area.
Advanced feature engineering, uncertainty quantification, and probabilistic forecasting methods
Energy markets and renewable generation forecasting domain expertise
Agile project management (Jira, Confluence)
Shift Hours: 8:00AM -5:00 PM CST

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

awsmachine learningagilescrumpythonapisqljiraai

Platform: jobdiva
Effort: medium