Southern Company is America’s premier energy company, serving approximately 4.2 million natural gas utility customers. The Data Scientist position involves developing and applying advanced analytics, machine learning, and AI to support pricing products, forecasting, and valuation, while improving model performance and collaborating with enterprise partners.
Accountable for domain AI outcomes and risk posture, including final technical approval for production readiness
Prioritize AI use cases based on business value, feasibility, and risk
Define and enforce SouthStar standards for model development, validation, monitoring, documentation, and responsible AI use, aligned with enterprise frameworks
Establish reusable AI/ML frameworks, templates, and best practices to accelerate delivery across teams
Lead cross-functional delivery of production AI solutions (automation, forecasting, decision support, AI assistants)
Drive workforce enablement (training, playbooks, coaching) to elevate AI adoption and productivity
Provide technical direction across multiple teams and functions, leading through influence rather than formal authority
Mentor junior staff on modeling practices and documentation; conduct technical reviews and guide complex problem-solving
Stay current on GenAI, NLP, and advanced ML trends and assess their applicability to SouthStar’s business
Lead end-to-end delivery of advanced analytics and AI solutions (design, build, deploy and monitor)
Define modeling standards, validation approaches, and monitoring thresholds; ensure explainability and audit readiness
Drive adoption by integrating models and AI tools into business workflows and decision processes
Partner with leadership to prioritize use cases, manage tradeoffs, and quantify business impact
Continuously improve data quality and governance practices to support scalable AI across markets
Design and develop statistical and ML models for business problems (forecasting, valuation, segmentation, anomaly detection)
Build scalable analytical pipelines and reusable datasets/features; implement validation checks
Create AI-enabled analytical tools (e.g., guided Q&A over curated data, automated insight generation) with measurable value
Develop dashboards and stakeholder-ready outputs; explain model results and tradeoffs
Collaborate cross-functionally to define requirements, success metrics, and adoption approach
Own delivery for assigned workstreams
Analyze and organize customer/market data for pricing, planning, and forecasting
Maintain and validate existing models and recurring reports; troubleshoot data issues
Develop baseline statistical or ML models under guidance (e.g., regression, classification, forecasting)
Use approved AI tools to automate routine analysis and reporting (e.g., templated notebooks, prompt-driven summaries)
Document assumptions, code, and data lineage; support audit and review requests
Continuously identify small improvements to data quality, model performance, and efficiency
Qualification
Required
Master's degree in analytics, statistics, data science, computer science, or a related quantitative field
10+ years of experience in analytics/data science, including a strong track record delivering enterprise-scale data and AI solutions
Extensive experience manipulating large data using SQL and platforms such as Databricks/Spark/Azure/AWS
Demonstrated success defining and scaling AI capabilities, frameworks, or platforms with strong execution
Expert-level modeling breadth (e.g., Natural Language Processing (NLP), deep learning, Bayesian methods, clustering, neural networks) and strong statistical foundations
Proven ability to define reusable AI/ML frameworks, standards, and governance guardrails
Experienced in complex integrations/migrations across data sources and platforms such as Databricks, Azure; sets architectural direction in partnership with IT
Demonstrated leadership in analytical model design/ development/ testing/ troubleshooting/ documentation for complex analytical systems
Strong stakeholder management capabilities and a proven ability to align teams
5-10 years of experience in analytics/data science, modeling, and large-scale data work
Hands-on experience delivering machine learning/AI solutions and/or production-level model deployment
Experience manipulating large databases using SQL and platforms such as Databricks/Spark/Azure/AWS
Advanced modeling breadth (supervised/unsupervised methods) and strong statistical foundations
Ability to design validation, monitoring, and retraining plans (drift detection, performance thresholds)
Strong troubleshooting and documentation skills for complex analytical systems
Technical leadership and stakeholder management; able to drive alignment across teams
Bachelor's degree in a quantitative field (e.g., mathematics, statistics, economics, data science, computer science, or similar)
3-5 years' experience in analytics/modeling and data processing
Demonstrated ability to build and manage models in a business environment
Experience working with large data using SQL and modern analytics platforms (e.g., Databricks/Spark/Azure/AWS)
Strong programming skills in Python or R; solid SQL proficiency
Experience with feature engineering, model evaluation, and performance tuning
Experience with dashboards/visualizations (e.g., Power BI, Tableau, SSRS) to communicate insights
Strong understanding of data governance basics (access, quality checks, and documentation)
0-2 years of experience (including internships/co-ops) in analytics, data, or modeling
Working knowledge of SQL and relational databases (e.g., SQL Server, Oracle, MySQL)
Hands-on programming for analysis (Python or R) and basic ML/statistical modeling
Ability to follow established standards for documentation, validation, and reproducibility
Able to communicate results clearly to technical and non-technical stakeholders
Preferred
PhD in one of the above disciplines; Project Management Professional (PMP) or equivalent leadership certification
PhD (or in progress) in one of the above disciplines
Master's degree (or in progress) in a quantitative discipline
Exposure to energy/utility markets or pricing/forecasting concepts (through coursework or experience)
Benefits
Competitive base salary
Annual incentive awards for eligible employees
Health, welfare and retirement benefits designed to support physical, financial, and emotional/social well-being
This position may also be eligible for additional compensation, such as an incentive program, with the amount of any bonus/awards subject to the terms and conditions of the applicable incentive plan(s).
Hybrid work schedule, 4 days per week, in the office/onsite, with 1 remote day from home and subject to change per business needs.
Southern Company headquartered in Birmingham, Alabama, is the shared services division of Southern Company.
