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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data science and data engineering, with a strong focus on financial data quality, model development, and stakeholder communication. Proven ability to lead teams, manage projects, and influence business decisions through data-driven insights.
Highest-signal resume keywords
Data ScienceData EngineeringMachine LearningTeam LeadershipStakeholder Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ArchitectureData PipelinesModel DevelopmentData QualityAdvanced AnalyticsAutomationExperimentationMonitoringDocumentationTechnical Debt Management
Soft Skills
CoachingCommunicationGrowth MindsetProblem FramingInfluencing Business Decisions
Industry Keywords
FinanceQuantitative DisciplineOperational SupportKnowledge SharingTechnical Leadership
About the role
Key responsibilities & impact- Lead a small, high-impact team of a data scientist and a data engineer supporting Finance
- Manage, coach, and develop team members through clear expectations, development plans, delegation, and ownership
- Set team strategy and priorities across strategic initiatives, recurring operations, model maintenance, knowledge coordination, and technical debt
- Provide technical leadership across data science and data engineering, including problem framing, modeling, data architecture, pipelines, testing, monitoring, documentation, and production readiness
- Identify and establish standards for AI, machine learning, automation, advanced analytics, experimentation, evaluation, interpretability, human oversight, privacy, and monitoring
- Improve financial data quality, lineage, observability, documentation, governance, and reliability
- Ensure models and analyses support financial planning, forecasting, driver understanding, and decision-making
- Establish operating mechanisms for intake, prioritization, roadmaps, reviews, incident response, documentation, knowledge sharing, and stakeholder communication
- Communicate data, model, and engineering implications, recommendations, risks, and trade-offs to technical, non-technical, Finance, and executive audiences
- Partner with Finance, Engineering, Data, Product, software engineering, and executive stakeholders
- Automate recurring tasks, improve service levels, and increase the team’s strategic contribution
Requirements
What you’ll need- Bachelor’s degree or above in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline, or equivalent practical experience
- Significant experience applying data science, machine learning, analytics, data engineering, or a combination of these disciplines to business problems
- Experience directly managing and developing technical professionals, ideally including both data scientists and data engineers or closely adjacent roles
- Strong professional foundation in either data science or data engineering, with demonstrated ability to work effectively across the other discipline
- Experience leading a portfolio of projects from problem definition through delivery, adoption, measurement, and ongoing operation
- Experience with data quality, data pipelines, analytical datasets, model development or maintenance, experimentation or evaluation, and production or operational support
- Demonstrated ability to use data and technology to influence business decisions and deliver measurable impact
- Strong communication and stakeholder-management skills, including the ability to explain technical concepts, uncertainty, and trade-offs to Finance and executive audiences
- Demonstrated growth mindset: actively seeks feedback, learns new technologies and domains, adapts to changing conditions, and creates an environment where the team does the same
- Ability to operate with a high degree of autonomy and ownership in an ambiguous, fast-changing environment
