Principal Data Scientist - Albuquerque, NM; Hybrid

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Salary Range: $ To $ Annually

The Principal Data Scientist is a senior practitioner leader who operates at the intersection of hands‑on analytical and modeling execution, applied research, client‑facing solutioning, and cross‑functional program leadership. This role is designed for a data scientist who can walk into any project environment, immediately understand what question needs to be answered and why, sequence the analytical work, align the teams, and deliver.

This is a hybrid position based out of our Albuquerque office.

At the Principal level, this person drives data science and AI/ML strategy for the organization, not just a single project. They set modeling standards, evaluate methodological and platform trade‑offs, lead reference architecture decisions for analytical and AI systems across engagements, and are the person RS21 turns to when a modeling or analytical decision is hard. They translate ambiguous client requirements into rigorous, defensible analytical approaches, own the full data science lifecycle from problem framing through model deployment and monitoring, and bridge the communication gap between business stakeholders, product teams, data engineers, and platform engineers with equal fluency.

This role further serves as an embedded technical program lead, with the discipline to decompose ambiguous initiatives into structured, sequenced delivery work, the systems thinking to connect every analytical task to its business outcome, and the ownership to keep multi‑workstream programs on track independently.

As a people manager, the Principal Data Scientist holds direct line management responsibility for a team of data scientists. They own hiring, performance management, career development, and day‑to‑day people leadership for their team, ensuring data scientists are growing technically while also being effectively staffed and supported across client engagements.

Critically, the Principal Data Scientist is a force multiplier. They raise the capabilities of those around them, train and coach junior and mid‑level staff, establish the patterns and practices RS21's data science function grows from, and actively contribute to RS21's business development and proposal efforts as a credible technical voice.

People Management

• Serve as the direct line manager for a team of data scientists, owning staffing, workload balance, and day‑to‑day people leadership.
• Conduct regular 1:1s, set goals, and deliver formal performance reviews and feedback that support each team member's growth and accountability.
• Own hiring decisions for the team, including interviewing, candidate evaluation, and onboarding planning for new data scientists.
• Identify and address performance issues proactively and fairly, partnering with HR and technical leadership as needed.
• Build individual development plans that align team members' career goals with RS21's technical roadmap and project needs.

Data Science & Modeling

• Drive RS21's data science and modeling strategy, evaluate statistical, machine learning, and AI methodologies across engagements and make organization‑wide recommendations.
• Design, build, and validate production‑grade predictive, statistical, and machine learning models that address well‑defined business and operational questions.
• Architect end‑to‑end modeling workflows with rigorous validation, bias and performance monitoring, and reproducibility built into the design from day one.
• Establish modeling standards, experimentation practices, and analytical norms that apply across RS21's project portfolio.
• Ensure model reliability, fairness, and performance across engagements, and hold teams accountable to those standards.

LLM Enablement & Applied AI

• Evaluate and select foundation model and modeling strategies for RS21's AI and LLM‑powered offerings; guide ethical AI approach across engagements.
• Design and implement analytical approaches that support LLM and AI use cases, including:
• Model evaluation,…