Data Scientist - Migration Intelligence

Role overview

This Data Scientist position focuses on migration intelligence, applying quantitative analysis to evaluate risk, validate data consistency, and guide end-to-end customer data migration projects. The role combines hands-on data engineering, technology scouting, and modeling to support customer engagements as well as internal platform and product development. It is based in Brooklyn, NY with the option to telecommute from anywhere in the continental United States.

Responsibilities

- Assess third-party tools, platforms, and emerging technologies relevant to data migration, data infrastructure, and AI-assisted workflows, including benchmarking, integration feasibility, and build-versus-buy analysis. - Build quantitative models and analytical frameworks that quantify migration risk, predict data quality issues, and verify consistency between source and target database environments. - Coordinate full-cycle delivery of customer migration projects, covering scoping, sequencing, milestone planning, risk and dependency management, and cross-functional execution. - Design, build, and maintain internal data pipelines that combine structured and unstructured sources for analytics, reporting, and operational workflows. - Codify lessons from the field into repeatable analytical playbooks, migration frameworks, and operational accelerators for the broader team. - Implement data quality monitoring, automated regression validation, and lineage analysis using Python and SQL to support both platform development and customer engagements. - Analyze cloud and multi-cloud data environments for cost, reliability, and integration trade-offs, producing recommendations that shape architectural and sourcing decisions. - Develop dashboards and unified reporting structures that turn disparate information into actionable insights for product, sales, and operations stakeholders. - Evaluate technology partner integrations and coordinate technically sound implementation of partner solutions. - Act as an internal subject matter resource on data pipeline evaluation and migration methodology, validating workflows and converting operational findings into structured product feedback.

Requirements

- Master's degree in Data Science, Applied Mathematics, or a closely related quantitative field. - At least two years of experience in Data Science, Technology Evaluation, or Applied Analytical roles. - Demonstrated experience assessing the performance of AI/ML technologies. - Strong proficiency with Python and SQL for building validation, monitoring, and lineage workflows. - Track record coordinating cross-functional delivery across internal teams, customers, and external partners.

Nice to have

- Hands-on experience evaluating cloud and multi-cloud environments for cost, reliability, and integration risk. - Experience converting analytical insights into platform or product improvements.

Benefits and work setup

- Base salary of $155,000 per year. - Brooklyn, NY hub with the option to telecommute from the continental U.S. - Stated commitment to equal opportunity employment and an inclusive, diverse workplace.