Data Scientist - Migration Intelligence

What You’ll Do

• Evaluate third-party tools, platforms, and emerging technologies relevant to data migration, data infrastructure, and AI-assisted workflows, including technical benchmarking and integration feasibility analysis, and build-versus-buy assessment.

• Develop and apply quantitative models and analytical frameworks to assess migration risk, predict data quality issues, and validate data consistency across source and target database environments throughout migration project delivery.

• Coordinate end-to-end delivery of customer data migration projects, including scoping, sequencing, milestone planning, risk identification, dependency management, and cross-functional execution across internal teams, customers, and external partners.

• Design, build, and maintain internal data pipelines and supporting infrastructure that integrate diverse structured and unstructured data sources for analytics and reporting and operational use cases.

• Develop repeatable analytical playbooks, migration frameworks, and data-driven operational accelerators based on hands-on project delivery experience.

• Implement data quality monitoring, automated regression validation, and lineage analysis workflows using Python and SQL to support platform development and customer migration engagements.

• Evaluate cloud and multi-cloud data environments for cost efficiency, reliability, and integration risk, producing analytical recommendations that inform architectural and sourcing decisions.

• Implement data models, dashboards, and internal reporting structures that unify multiple sources of information into actionable insights for product, sales, and operational teams.

• Support technology partnerships and external cooperation efforts by assessing integration opportunities and coordinating the technically sound implementation of partner solutions.

• Act as an internal subject matter expert for data pipeline evaluation and migration methodologies, validating analytical workflows on internal data and translating operational findings into structured product feedback.

Requirements

• A 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.