Principal Data Scientist

Role Overview

The Principal Data Scientist provides senior technical leadership in the design, development, deployment, and responsible use of advanced analytics, machine learning, and generative AI solutions. This role transforms complex enterprise and customer data into actionable intelligence, production-ready models, and reusable analytical capabilities that improve customer experiences, business decisions, and operational outcomes.

What You Will Do

Develop production-quality solutions using Databricks, Python, PySpark, SQL, and related cloud technologies, ensuring that analytical work is scalable, reusable, testable, documented, and supportable. Design and evaluate solutions that interact with large language models, including prompt-based applications, retrieval-augmented generation, grounded question answering, summarization, classification, and agentic or workflow-oriented patterns where appropriate.

Why It Might Be a Fit

The successful candidate will demonstrate understanding and application of the Southern Company behaviors: Unquestionable Trust, Superior Performance, and Total Commitment. Acts ethically and protects customer, employee, and company data. Delivers results with accountability, sound judgment, and attention to quality.

Requirements

• Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, Machine Learning, or a closely related quantitative field
• Minimum of 6 years of experience working with large, diverse, and sensitive datasets and translating analytical results into measurable business value
• Extensive progressive experience applying data science, machine learning, advanced analytics, or artificial intelligence to complex business problems
• Demonstrated experience developing, validating, deploying, monitoring, and improving analytical and machine learning models in enterprise environments
• Advanced proficiency in Python and PySpark for data preparation, exploratory analysis, feature engineering, statistical analysis, machine learning, and production-scale model development
• Strong hands-on knowledge of Databricks, including collaborative development, distributed computing with Apache Spark, ML lifecycle practices, model tracking, governed data access, and deployment patterns
• Advanced knowledge of statistical methods, experimental design, causal reasoning, predictive modeling, forecasting, classification, clustering, anomaly detection, and model evaluation
• Strong knowledge of large language models, including prompt design, model interaction patterns, retrieval-augmented generation, embeddings, vector search, evaluation, grounding, guardrails, and responsible AI considerations
• Ability to design reliable model evaluation approaches for predictive and generative AI solutions, including quality, accuracy, bias, explainability, safety, drift, performance, and business-impact measures
• Strong SQL and data engineering skills, including experience integrating structured and unstructured data across enterprise platforms and building repeatable analytical pipelines
• Knowledge of cloud-based data and AI platforms, software development practices, version control, automated testing, APIs, CI/CD, and MLOps or LLMOps practices
• Ability to debug and troubleshoot complex data, code, model, and performance issues across the analytical lifecycle
• Working knowledge of data governance, data privacy, security, model risk, ethical AI, and the appropriate handling of customer and enterprise data
• Leadership and business skills, including ability to identify and shape high-value data science and AI opportunities, provide technical direction, establish standards, influence without direct authority, and mentor data scientists, data engineers, analysts, and business partners

Benefits

• Competitive base salary
• Annual incentive awards for eligible employees
• Health, welfare, and retirement benefits
• Incentive program
• Dental insurance
• Vision insurance
• PTO
• Retirement
• Learning budget
• Parental leave
• Wellness
• Visa/relocation support
• Remote flexibility
• Stipends
• Bonus/commission
• Paid holidays