Data Analyst; Machine Learning and Generative AI

Job Summary

Has worked in an Agile environment that uses the Scrum Methodology and is experienced with the related events and artifacts.

Effectively worked in a global, team‑based environment with team members in various locations and countries.

Demonstrated ability to work across business, BI, ML, Data Ops, and Architecture teams to align on standards, data contracts, SLAs, and shared operating mechanisms.

Roanoke, Texas

Contract

$51 - $52 per hour

8 am to 5 pm

Bachelor's

• Collaborating with business stakeholders to gather and analyze business and functional requirements and confirm these via meaningful artifacts (Business Requirements documents, process flows and data flow diagrams, use cases, etc.)
• Translating business goals into end‑to‑end system and data requirements, including field‑level definitions, data rules, and non‑functional requirements.
• Partnering with BI engineers, Data engineers and ML Engineers to define and maintain detailed source‑to‑target data mappings, interface contracts, and data lineage from source systems through integration layers to downstream warehouses and reports.
• Contributing to the documentation and maintenance of end‑to‑end data and process lineage (from Oracle/Snowflake/S3 through transformations, BI assets and ML pipelines to operational workflows), and coordinating impact analysis for upstream schema or logic changes.
• Performing cost‑benefit analyses to ensure technology investments for the given business requirements are strategically aligned, financially sound, and deliver maximum business value.
• Converting business requirements into actionable delivery plans with defined milestones and timelines for both system and data work.
• Identifying and managing risks and dependencies for planned work.
• Implementing delivery plans through quarterly planning and backlog management.
• Managing product backlogs using collaborative tools including JIRA, Confluence, PowerPoint, Excel, and SharePoint.
• Translating complex business and data requirements into user stories with well‑defined business value and acceptance criteria and test conditions (including data validation and report acceptance).
• Leading team refinement sessions to ensure stories are clear and ready for sprint planning.
• Defining story acceptance tests in collaboration with the team, applying Acceptance Test Driven Development (ATDD) principles during refinement.
• Ownership of user story sign‑off, ensuring the delivery meets the requirements and has passed all tests (automated and manual).
• Proactively identifying opportunities for process and system improvements to extend the value delivered to your business partners.
• Where needed – Participation in end‑to‑end test activities to ensure functionality is working per the requirements.

• Financial services industry knowledge and experience is highly desirable; investment management and/or wealth management domain knowledge is a plus.
• Strong experience working with data in support of analytics and reporting use cases.
• Hands‑on experience with relational databases and SQL for analysis, profiling, and data validation.
• Understanding of data modeling concepts (e.g., star and snowflake schemas, dimensions and facts) and how they support BI/reporting.
• Experience defining or supporting BI/reporting solutions (e.g., Power BI, Tableau, or similar), including KPIs, drill‑downs, and filters.
• Experience working with or around ML/LLM solutions (or strong interest and aptitude to learn), including helping to define data requirements, success criteria, and basic monitoring/adoption needs for models and AI‑driven reports in partnership with ML Engineers.
• Excellent written and verbal communication skills.
• Strong analytical and problem‑solving skills with the ability to reason about complex systems and data flows.
• Able to understand the technology and software architecture of an application.
• Experience with various tools that assist in analysis and testing including SQL Developer, Insomnia, Kafka – Offset Explorer, and Datadog for data validation and debugging, Jira and Confluence.
• Willingness to dive in and understand code for analysis and…