Data Scientist

Data Scientist

12+ Months Contract

ONSITE in St. Paul, South Florida, or REMOTE

MUST HAVE:

Strong Communication: Able to clearly explain a past technical project in 1–2 minutes to a non-technical audience, including the business problem, approach, and measurable impact.

AI-Enabled Development Workflow: Actively uses AI-assisted development tools (e.g., Claude, GitHub Copilot) as part of daily technical workflows for coding, debugging, documentation, or prototyping.

Independent Technical Leadership: Demonstrated experience independently owning and delivering complex technical solutions in fast-paced environments, including problem framing, technical decision-making, and execution using physics-based modeling, machine learning, optimization, and/or AI techniques.

Cross-Functional Development Experience: Experience working on cross-functional teams involving both Data Science and Software Engineering, including collaboration on production systems, deployed models, or shared technical deliverables.

Business Impact and Industry Experience: 10+ years of experience in industry (preferably including energy, utilities, industrials, logistics, or other operational domains) with demonstrated examples of measurable business impact from technical work.

The Data Scientist level 3 is a senior technical leader and strategic contributor responsible for driving high-impact, enterprise-level analytics and AI initiatives, shaping modeling standards, and influencing long-term data strategy.

This role leads large-scale, cross-functional programs; architects advanced machine learning and AI solutions; defines modeling best practices and governance frameworks; and provides technical mentorship across the organization.

Responsibilities also include evaluating emerging technologies, guiding enterprise data roadmaps, and presenting insights and strategic recommendations to executive leadership. Candidates should have an advanced degree in a quantitative field, 11-15 years of progressive data science experience, expert proficiency in Python or R for scalable modeling and enterprise integration, experience leading complex modeling initiatives, and deep expertise in advanced ML techniques such as deep learning, optimization, NLP, time series, and causal inference.

Preferred qualifications include experience managing cross-functional technical teams, contributions to research or open-source work, and influence on enterprise architecture decisions, along with advanced use of AI coding assistants. Key competencies include strategic thinking, executive communication, enterprise-level influence, and deep technical innovation.