Senior Applied Data Scientist

Senior Applied Data Scientist - AI & Advanced Analytics

We will specifically be seeking Applied Data Scientists who demonstrate the following characteristics and experience:

Strong Communication Skills

• Ability to clearly explain a past technical project in 1-2 minutes to a non-technical audience .
• Can effectively communicate:
• The business problem or objective
• The technical approach and methodology
• The candidate's specific contribution
• The measurable business or operational impact
• Candidates should be able to translate complex technical concepts into clear, concise business language.

AI-Enabled Development Workflow

• Actively uses AI-assisted development tools as part of their day-to-day technical workflow.
• Other AI-powered coding and development tools
• Demonstrated use of AI tools for activities such as:
• Coding
• Documentation
• Prototyping
• Technical problem-solving
• Candidates should be able to explain how AI-assisted tools have improved or accelerated their development workflow.

Independent Technical Leadership

• Demonstrated ability to independently own and deliver complex technical solutions in fast-paced environments.
• Experience taking ownership of projects from problem definition through technical execution and delivery .
• Strong technical decision-making skills, including the ability to evaluate approaches, make tradeoffs, and select appropriate methodologies.
• Hands-on experience applying one or more of the following:
• Physics-based modeling
• Machine learning
• Optimization

Cross-Functional Development Experience

• Proven experience working on cross-functional teams that include both Data Science and Software Engineering .
• Experience collaborating with software engineers and other technical stakeholders to move data science solutions from development into production.

Familiarity with:

• Production systems
• Deployed machine learning models
• Shared technical deliverables
• Productionization and operationalization of data science solutions
• Ability to effectively bridge the gap between data science, software engineering, and business stakeholders.

Business Impact & Industry Experience

• 10-15+ years of industry experience in applied data science, advanced analytics, engineering, or related technical disciplines.
• Preference for candidates with experience in operational industries such as:
• Energy
• Utilities
• Logistics
• Manufacturing
• Other asset-intensive or operational environments
• Demonstrated history of applying technical solutions to real-world business and operational problems .

Strong examples of measurable impact, such as:

• Cost reduction
• Increased operational efficiency
• Improved reliability or performance
• Automation
• Candidates should be able to clearly connect their technical work to measurable business outcomes .