Data Scientist

Job Title: Senior Data Scientist

Locals needed.
Candidates must currently reside in the Raleigh, Durham, or Chapel Hill, North Carolina area (Triangle region).
All requirements are mandatory.
Duration: 12+ Months
Work Arrangement: Hybrid
Interview Mode: Webcam or In-Person Interview
Submission Due: 10/23/2026

Candidate Location & Onsite Requirements
Candidates must currently reside in the Raleigh, Durham, or Chapel Hill, North Carolina area (Triangle region).
The candidate must be available to report onsite on the first day to collect equipment.
The position is primarily remote; however, occasional onsite attendance at a Triangle-area office may be required for in-person responsibilities as directed by management.
Candidates must be able to accommodate these onsite requirements.

Job Description: We are seeking an experienced Senior Data Scientist to support the development and implementation of enterprise data strategy, governance, and modern data architecture practices. This role will focus on establishing consistent data management standards across technical teams and business units, improving data quality, and enabling scalable data ingestion, transformation, and analytics solutions.

The ideal candidate will have extensive experience in enterprise data governance, data architecture, and modern cloud data platforms, along with the ability to work independently and collaborate with business and technical stakeholders to establish foundational data management practices.

Responsibilities
Collaborate with business stakeholders, application teams, database administrators, data engineers, analytics teams, and project teams to understand data requirements and identify opportunities for improvement.
Facilitate discussions to identify authoritative data sources, establish common business definitions, and improve understanding of enterprise data assets.
Define and standardize enterprise data elements, business rules, and data lineage across business units.
Implement practical data governance, metadata management, lineage tracking, and data quality practices across projects.
Identify opportunities to standardize and reuse data ingestion, transformation, cleansing, and validation patterns using Azure Data Factory and Azure Databricks.
Develop and maintain an inventory of enterprise data assets, including data owners, data stewards, business definitions, and system relationships.
Document end-to-end data flows across applications, platforms, and reporting solutions to improve transparency and architectural clarity.
Participate in data architecture and solution design discussions to promote consistency, scalability, and reuse across enterprise data solutions.
Establish foundational data management practices and enterprise standards in environments where formal data governance frameworks may not yet exist.

Required Qualifications
At least 3 years of experience defining and standardizing enterprise data elements, data lineage, and business rules across business units.
At least 3 years of experience collaborating with business teams to translate data requirements into consistent enterprise data standards.
At least 3 years of experience implementing data governance practices, including metadata management, data lineage, and data quality, across projects.
At least 3 years of experience documenting end-to-end data flows across systems to improve data transparency and architecture clarity.
Advanced knowledge of enterprise data strategy, data governance, and modern data architecture.
Hands-on experience with cloud-based data platforms and data engineering solutions, particularly Azure Data Factory and Azure Databricks.
Strong stakeholder communication, analytical, documentation, and problem-solving skills.
Ability to work independently, exercise sound judgment, and lead enterprise data initiatives across technical and business teams.