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Data QA Manager

Lux Research is a rapidly growing company providing strategic advice and on-going intelligence on emerging technologies. Leaders in business, finance, and government rely on us to help them make informed decisions around innovation and technology. Within Lux’s software development team, you’ll find new and uniquely interesting problems to solve. You’ll analyze data from uncommon sources and uncover insights on emerging technologies in fields like advanced materials, renewable energy, and robotics.

Lux Research is looking for an experienced data QA manager to lead our efforts on data quality. Specifically, for our data covering technology start-ups and other innovative companies: You will be responsible for managing a small team of data QA specialists, who work to ensure the information we have collected about those companies is accurate and presentable. You will also be communicating and collaborating with Lux Research’s software development team to provide feedback on opportunities to improve our automated data ingestion and clean-up, as well as with Lux Research’s analyst team to understand domain-specific nuances within each industry and technology area that we cover.

What you’ll do:

  • Be responsible for improving the quality of data and descriptions of companies included in Lux Research’s database.
  • Develop and maintain data curation protocols and processes, including identifying and defining logic and thresholds to detect data anomalies.
  • Perform root cause analysis of data discrepancies and develop action plans to address such issues.
  • Manage data QA specialists that manually correct data and descriptions as needed.
  • Work with counterparts in other parts of the software development team and more broadly at Lux, including our syndicated research arm, to better understand data-quality-related issues and possible solutions.

What we look for:

  • 3+ years of experience leading data quality assurance processes on large datasets, including structured and unstructured data.
  • Ability to understand complex data models and data relationships, as well as ability to follow data transfer and analytics through multiple layers.
  • Experience managing a small team; remote management experience a huge plus.
  • Working knowledge of databases and software development – enough to communicate effectively with data engineers and back-end programmers (topics like data warehousing, ETL, and data analytics).
  • Some familiarity with science and engineering related topics, particularly in the context of emerging technologies and start-ups.
  • Great communication and organizational skills are essential, including the ability to meet deadlines in a fast-paced, collaborative workplace.
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