Data Scientist, Dataset Assessment Lead

TekWissen • Sunnyvale, CA

6d • Hybrid

About The Position

Accenture is seeking a Data Scientist, Dataset Assessment Lead for a three-month temporary assignment supporting Reality Labs Supply Chain. The project is establishing an NPI data foundation for AI-enabled supply chain workstreams, including product change management and PRQ qualification, capacity and Capex planning, in-market quality and incident management, and end-of-manufacturing planning. The role will assess the datasets those workstreams depend on and establish an inventory and quality baseline.

The lead will document dataset sources, owners, refresh cadence, lineage, and downstream consumers; interview data owners and operational and engineering stakeholders to understand how datasets are produced and used; and assess datasets using a seven-dimension data quality framework. The role will also document repeatable assessment methods, prioritize remediation, identify which datasets are ready for AI or automation, and present findings to Supply Chain leadership and the incoming Data Engineer.

Requirements

• At least 5 years of experience in data science, data quality, or data governance roles.
• Demonstrated experience building a dataset inventory or conducting a data quality assessment at enterprise scale.
• Working knowledge of supply chain, manufacturing, or NPI processes sufficient to credibly assess forecast, capacity, yield, or inventory datasets.
• Strong SQL and Python (pandas) skills for profiling and statistical quality checks.
• Excellent stakeholder interviewing and written synthesis skills; comfortable leading conversations with senior cross-functional partners.
• Ability to deliver a scoped assessment within an eight-week window with minimal ramp.

Nice To Haves

• Familiarity with Meta's data stack, including Hive/Presto, Databricks, Scuba, and Unidash, and with PLM/MES data such as Teamcenter and factory MES.
• Experience with data catalog or metadata management tooling and formal data quality frameworks such as DAMA-DMBOK or similar.
• Hardware NPI or consumer electronics supply chain background.

Responsibilities

• Build an authoritative inventory of datasets supporting NPI and supply chain processes, including source systems, owners, refresh cadence, lineage, and downstream consumers.
• Conduct structured interviews with data owners, OPMs, manufacturing operations, quality, and engineering to understand how datasets are produced and used.
• Score each dataset against the seven-dimension data quality framework, providing evidence and a defensible rationale for each score.
• Document the scoring rubric, interview guide, and intake template so the assessment can be repeated after the engagement.
• Deliver a prioritized remediation backlog identifying datasets ready for AI or automation, datasets requiring work, and the required work.
• Present a findings readout to Supply Chain leadership and hand off findings to the incoming Data Engineer.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed