Principal Data Scientist - AI, Machine Learning, Fraud Detection

RHODES FINANCIAL SERVICES LLC•Charlotte, NC

8d•Remote

About The Position

The Principal Data Scientist is a senior technical leader who drives advanced machine learning and data science initiatives across TaxSlayer. The role combines hands-on technical expertise with strategic influence, owning complex ML projects end to end, presenting recommendations to leadership, leading technical discussions, and serving as an authority on modeling approaches. The position partners with Product, Engineering, Finance, and Marketing to address high-impact business problems, particularly in fraud detection, customer intelligence, and risk modeling. The role develops and deploys machine learning models and production systems, including real-time scoring pipelines, and evaluates emerging technologies such as large language models, generative AI, and agentic systems. It also establishes modeling and deployment practices, builds scalable data and modeling infrastructure, monitors production models and business outcomes, and ensures compliance with regulatory, privacy, security, and governance requirements. This is a fully remote, US-based role for people living in approved hiring states: Georgia, South Carolina, North Carolina, Florida, or Tennessee. Occasional US travel is required, estimated at four to six times per year. Work is performed in a standard office environment, with extended computer use.

Requirements

Master's or PhD degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or Physics, or equivalent 8+ years of hands-on industry experience as a Data Scientist, Machine Learning Engineer, or similar role.
Experience presenting complex work to senior audiences.
Demonstrated success leading multiple end-to-end machine learning projects from ideation through production deployment and monitoring, including presenting outcomes and leading stakeholder discussions.
Track record of self-initiated, high-impact projects executed with full ownership and minimal oversight.
Very high proficiency in multiple machine learning methods, including supervised learning, unsupervised learning, and deep learning.
Advanced expertise in SQL and Python, with strong software engineering fundamentals including version control, testing, code design, and distributed systems concepts.
Strong proficiency in AI technologies, including experience evaluating, fine-tuning, or deploying LLMs and generative AI systems in production.
Strong experience with MLOps, model deployment, monitoring, and serving in production environments; hands-on familiarity with cloud platforms such as Snowflake, Databricks, AWS, GCP, or Azure.
Strong understanding of statistical analysis, experimental design, A/B testing, hypothesis testing, and causal inference.
Experience building real-time or near-real-time scoring systems and production ML pipelines.
Excellent communication and presentation skills, including the ability to explain complex concepts to technical and non-technical audiences and lead discussions without heavy coaching.
Strong cross-functional collaboration and stakeholder management skills; ability to influence decisions and drive adoption across Product, Engineering, Finance, and business teams.
Ability to work at a computer for extended periods.
Must be based in the US and live in an approved hiring state: Georgia, South Carolina, North Carolina, Florida, or Tennessee.
Occasional travel within the US is required, estimated at four to six times per year.

Nice To Haves

Experience in financial services, tax preparation, SaaS, fintech, or e-commerce.
Hands-on experience building fraud detection, anomaly detection, or risk modeling systems.

Responsibilities

Own end-to-end delivery of strategic data science projects, from problem definition through production deployment, monitoring, and optimization; lead scoping discussions and present results.
Develop and deploy machine learning models for fraud detection, risk assessment, anomaly detection, customer segmentation, and churn prediction, including reliable real-time scoring pipelines.
Lead fraud detection initiatives, design detection algorithms, collaborate with compliance and investigation teams, and improve model performance as fraud patterns evolve.
Evaluate and apply emerging AI and machine learning technologies, including LLMs, generative AI, and agentic systems.
Define and document best practices for model development, testing, and deployment, and present them to stakeholders.
Design and build scalable data pipelines, feature engineering frameworks, and reusable modeling infrastructure.
Monitor production model performance, data quality, and business outcomes; troubleshoot degradation and drive continuous improvements.
Partner with Product, Engineering, Finance, and Marketing to define analytical requirements, establish success metrics, and deliver recommendations.
Present analytical findings and strategic recommendations to executives and business stakeholders; explain technical concepts and promote data-driven strategies.
Ensure models and analytical processes comply with regulatory, privacy, security, and governance requirements; collaborate with compliance and legal teams as needed.
Stay current with data science, ML, and AI trends; identify, prototype, and recommend innovations.
Contribute to documentation, best practices, architectural decisions, and reusable code libraries.
Independently identify and execute high-impact strategic initiatives with minimal direction, align stakeholders on priorities, and improve data science processes, tooling, and infrastructure.

Benefits

Flexible remote and/or hybrid work options when possible, depending on the role.
Generous PTO bank for exempt salaried employees.
Paid holidays.
Medical insurance.
Dental insurance.
Vision insurance.
401(k) with a 150% match on up to 3% contribution.
Performance-based bonus and salary review process.
Wellness program.
Life insurance for employees.
Long-term and short-term disability insurance.
Critical illness insurance.
Accident insurance.
Education assistance.
Company-paid parking.
On-site fitness facility.
Company store.