Data Scientist

Data Scientist – Advanced Metering Infrastructure (AMI) Analytics

Locations (Multiple):
Qualified candidate can report to ANY of these 3 locations.

• Alabama Power Company Corporate Headquarters – Birmingham, AL
• Georgia Power Company Corporate Headquarters – Atlanta, GA
• Mississippi Power Corporate Headquarters – Gulfport, MS

Job Summary: The Data Scientist within APC Power Delivery’s AMI Analytics team plays a strategic role in advancing data-driven decision-making and operational efficiency across business units. This position blends analytical depth, technical expertise, and business insight to deliver scalable AI solutions that support AMI initiatives. The successful candidate will lead data science efforts, assess feasibility of advanced analytics use cases, and establish robust frameworks for AI deployment and monitoring within the AMI data domain.

• AI/ML Strategy & Use Case Development:
  • Identify and evaluate AI/ML opportunities aligned with AMI business objectives.
  • Stay current on emerging technologies and educate the team on their practical applications.
• Algorithm Design & Model Optimization:
  • Develop and refine machine learning models to solve complex problems using enterprise-scale data.
  • Continuously adopt new tools and techniques to enhance model performance and scalability.
• Framework Development & MLOps Integration:
  • Architect and implement an AMI-specific AI development framework under the AMI Governance Committee.
  • Integrate MLOps practices for seamless cloud deployment, monitoring, and lifecycle management.
  • Collaborate with cross-functional teams to provision ETL workflows and CI/CD pipelines.
• Documentation & Reporting:
  • Produce clear, comprehensive documentation to support transparency, reproducibility, and stakeholder communication.
• Collaboration & Mentorship:
  • Partner with end-users to understand analytical needs and co-create data-driven solutions.
  • Mentor team members to foster skill development and promote a culture of continuous learning.

• Master’s degree in Computer Science, Mathematics, Statistics, Data Analytics, Data Science, Machine Learning, or Artificial Intelligence.
• Minimum 5 years of experience in a technically focused, data-driven environment building supervised and unsupervised machine learning models.

• Programming & Data Engineering:
  Proficient in Python and R; working knowledge of Spark, Pandas, T-SQL, and PL-SQL.
• Model Development:
  Skilled in building predictive and prescriptive models, feature engineering, and ML algorithms.
• Cloud & Integration:
  Experience with Azure-based ML deployment, data migration, and integration across diverse datasets.
• Generative AI & LLMs:
  Familiarity with Generative AI and Large Language Models; hands‑on experience is a plus.
• Debugging & Optimization:
  Strong analytical skills for monitoring and troubleshooting data pipelines and solutions.
• Communication & Influence:
  Ability to translate technical concepts into actionable business insights and influence decisions across organizational levels.
• Consulting &
  
  Collaboration:
  
  Proven ability to work cross‑functionally and deliver strategic recommendations through data storytelling.
• Learning & Adaptability:
  Self‑driven learner with awareness of industry trends and emerging technologies.
• Multitasking & Prioritization:
  Capable of managing multiple projects, adapting to shifting priorities, and delivering results in a dynamic environment.

• Innovation and results orientation
• Strategic thinking with an enterprise mindset
• Commitment to continuous improvement and development of others
• Strong partnership‑building skills
• Ability to work independently and collaboratively
• Decisiveness and agility
• High ethical standards
• Being on‑site at the HQ office 4 days a week

Alabama Power provides safe, reliable, and affordable electricity to 1.5 million customers across the lower two-thirds of Alabama.

For more information, visit  and connect with the company on Facebook (), Twitter (), Linked In (), and Instagram ().

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