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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data migration, data infrastructure, and AI-assisted workflows, with a strong focus on developing quantitative models for risk assessment and data quality validation. Proficient in coordinating complex data migration projects and implementing data quality monitoring and reporting structures.
Highest-signal resume keywords
Data Migration Project CoordinationQuantitative Risk AssessmentPython ProgrammingSQL ProficiencyAI/ML Technology Evaluation
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 MigrationData InfrastructureQuantitative ModelingData Quality MonitoringIntegration Feasibility AnalysisTechnical BenchmarkingData Pipeline DevelopmentAutomated Regression ValidationData Model ImplementationDashboards Development
Soft Skills
Cross-Functional CollaborationRisk IdentificationDependency ManagementCommunication
Tools & Technologies
Cloud Data EnvironmentsMulti-Cloud SolutionsData Analytics Tools
Certifications & Qualifications
Master's Degree in Data ScienceMaster's Degree in Applied Mathematics
Industry Keywords
Data ScienceTechnology EvaluationApplied AnalyticsAI/ML TechnologiesData Quality Issues
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- Evaluate third-party tools, platforms, and emerging technologies relevant to data migration, data infrastructure, and AI-assisted workflows
- Perform technical benchmarking, integration feasibility analysis, and build-versus-buy assessments
- Develop and apply quantitative models to assess migration risk, predict data quality issues, and validate data consistency across source and target databases
- Coordinate end-to-end customer data migration projects, including scoping, sequencing, milestone planning, risk identification, dependency management, and cross-functional execution
- Design, build, and maintain internal data pipelines and supporting infrastructure integrating structured and unstructured data sources
- Develop analytical playbooks, migration frameworks, and data-driven operational accelerators
- Implement data quality monitoring, automated regression validation, and lineage analysis workflows using Python and SQL
- Evaluate cloud and multi-cloud data environments for cost efficiency, reliability, and integration risk
- Implement data models, dashboards, and internal reporting structures
- Support technology partnerships and external cooperation efforts by assessing integration opportunities and coordinating partner-solution implementation
- Act as an internal subject matter resource for data pipeline evaluation and migration methodologies
- Translate operational findings into structured product feedback
Requirements
What you’ll need- Master's Degree in Data Science, Applied Mathematics, or a closely related quantitative field
- At least 2 years of previous experience in Data Science, Technology Evaluation, or Applied Analytical roles
- Experience must include performance assessment of AI/ML technologies
- Must be able to telecommute from the continental U.S.
Benefits
Comp & perks- Equal opportunity employment
- Inclusive and diverse work environment
- Respectful workplace where employees are valued and unique perspectives are respected and celebrated