🚀 Principal Data Scientist [On-Site, Cities Listed In Posting]

Principal Data Scientist (On-Site, Cities Listed In Posting)

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Job Description

At Regions, the Principal Data Scientist is a visionary and hands‑on practitioner that supports the Data Science team by deepening technical bench strength across Machine Learning (ML), MLOps and GenAI. This position will drive the development of scalable, efficient, and reliable data‑science capabilities that elevate the entire team’s productivity and impact. This includes advancing model lifecycle management, establishing best‑in‑class practices, designing ML pipelines, and guiding the adoption of emerging technologies like Large Language Models (LLMs) and Generative‑AI. The candidate should have comprehensive knowledge of end‑to‑end data science modeling lifecycles and a strong track record of successfully delivering complex data science projects.

Primary Responsibilities

• Develops and leads execution of the research roadmaps for advanced AI capabilities such as LLM, GenAI, Retrieval‑Augmented Generation (RAG), Agents, and Computer Vision.
• Stays at the cutting edge of ML/AI literature and practices.
• Periodically evaluates the design of existing modeling and MLOps and identifies opportunities for improvement.
• Serves as a technical Subject Matter Expert (SME) on modeling techniques, feature engineering, pipeline orchestration, performance optimization and testing.
• Partners with other data scientists, engineers and product teams to define technical standards, influence solution‑design decisions, and raise the bar on solution quality.
• Champions MLOps excellence across the team, including CI/CD for ML, automated testing, monitoring, model versioning and rollback strategies.
• Designs and promotes implementation of reusable codes, tools and frameworks for model development, training, deployment, monitoring and governance.
• Drives complex, high‑impact modeling projects from ideation to production, especially where advanced techniques (e.g. NLP, GenAI, LLMs) can drive strong business value.
• Leverages statistical analysis, machine learning (ML) and deep learning (DL) techniques, collaborating with various lines of businesses to design data products that enhance profitability, mitigate risks, and drive customer engagement across all touchpoints.
• Leverages cloud‑based analytical platforms to build data analytics solutions.
• Extracts actionable insights from data to support data‑driven decision‑making processes.
• Collaborates with risk management and compliance teams to ensure compliance with internal and external regulatory requirements.
• Fosters a culture of innovation and continuous improvement within the team.

Requirements

• PhD degree in a quantitative or analytical field such as Statistics, Mathematics, Physics, Computer Science, Engineering, or a related discipline and four (4) years of relevant experience.
• Master’s degree in a quantitative or analytical field such as Statistics, Mathematics, Physics, Computer Science, Engineering, or a related discipline and six (6) years of relevant experience.
• Bachelor’s degree in a quantitative or analytical field such as Statistics, Mathematics, Physics, Computer Science, Engineering, or a related discipline and eight (8) years of relevant experience.
• Eight (8) years of experience in Machine Learning, with experience in GenAI, LLMs and frameworks such as Hugging Face Transformers and LangChain.
• Eight (8) years of programming experience in Python, PySpark, SQL and modern ML Libraries (e.g. Scikit‑learn, TensorFlow, PyTorch).
• Six (6) years of hands‑on experience with Big Data tools and platforms such as Hadoop, Spark, Hive, MLFlow or Kafka.
• Six (6) years of hands‑on experience with cloud‑based analytics platforms such as Amazon Web Services (AWS) SageMaker, Azure Machine Learning Studio, Google Cloud AI Platform, Snowflake or Databricks.

Preferences

• Five (5) years of experience in Agile Software Development Lifecycle.
• Five (5) years of experience influencing, guiding, or providing technical direction to other data scientists or cross‑functional team members. Background in banking and/or other financial services.
• Experience in RAG and integrating frontier models such as LangChain, llamaIndex, Anthropic, Bedrock, GPT, or Ollama.
• Experience with Docker/Kubernetes.
• Hands‑on experience with techniques for text parsing, sentiment analysis, and the use of generative models such as Generative Pre‑trained Transformer (GPT), Variational Autoencoders (VAE), and Generative Adversarial Networks (GANs).

Skills and Competencies

• Ability to continue research and learn new systems as needed.
• Ability to partner with stakeholders to identify business challenges and design solutions.
• Ability to research, analyze data, and derive facts.
• Ability to work under pressure and meet deadlines.
• Deep understanding of statistical and predictive modeling concepts, machine learning approaches, clustering and classification techniques, or recommendation and optimization algorithms.
• Experience delivering and scaling models in production.
• Experience planning, managing, and delivering data science projects, including risk identification and mitigation.
• Strong verbal, written communication, and organizational skills.
• Strong work ethic and self‑motivation.

On‑Site Requirements

This position is intended to be onsite, now or in the near future. Associates will have regular work hours, including full days in the office three or more days a week. The manager will set the work schedule for this position, including in‑office expectations. Regions will not provide relocation assistance for this position, and relocation would be at your expense. The locations available for this role are Birmingham, AL, Atlanta, GA or Charlotte, NC.

Regions will not sponsor applicants for work visas for this position at this time. Applicants for this position must currently be authorized to work in the United States on a full‑time basis.

Employment Type

Full time.

Benefits

• Paid Vacation / Sick Time
• 401(k) with Company Match
• Medical, Dental and Vision Benefits
• Disability Benefits
• Health Savings Account
• Flexible Spending Account
• Life Insurance
• Parental Leave
• Employee Assistance Program
• Associate Volunteer Program

Equal Opportunity Employer

Equal Opportunity Employer/including Disabled/Veterans.

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