Data Scientist - Migration Intelligence

Datafold• ,

1d•$155,000•Remote

About The Position

Datafold, Inc. is seeking a Data Scientist - Migration Intelligence in Brooklyn, NY. This role involves evaluating third-party tools, developing quantitative models for migration risk assessment, coordinating data migration projects, and designing data pipelines. The position also includes developing analytical playbooks, implementing data quality monitoring, evaluating cloud environments, and supporting technology partnerships. The Data Scientist will act as an internal subject matter expert on data pipelines and migration methodologies.

Requirements

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.

Responsibilities

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 resource for data pipeline evaluation and migration methodologies, validating analytical workflows on internal data and translating operational findings into structured product feedback.