Data Analysis Specialist
1 month ago
LGC Standards is a division of LGC Group, the UK’s designated National Measurement Institute for chemical and bioanalytical measurements. We are a leading global manufacturer and service provider of quality assurance and research tools, supporting analytical needs in more than 120 countries worldwide. Our wide range of reference materials and proficiency testing schemes is complemented by our experience in outsourcing and customs, enabling us to adapt quickly to provide tailored solutions that meet our customers’ analytical needs. p>Job Description
Are you passionate about translating complex product data into actionable insights? Are you detail-oriented and thrive in a role that requires meticulous database management? Join our team as a Scientific Data Analyst and play a pivotal role in ensuring the accuracy and integrity of our product data management processes.
- Data Accuracy Advocate: As a Scientific Data Analyst, you will be the gatekeeper of data accuracy. You'll be responsible for timely and precise updates to our databases, ensuring that new and existing product information is up-to-date and reflective of the latest research and developments.
- Investigative Expertise: You will be our go-to person for sourcing, collecting, and validating data from various third-party sources. Your keen attention to detail and systematic approach will be invaluable in cross-referencing data with inputs from product managers, guaranteeing the highest data quality standards.
- Chemistry Collaboration: Assist your fellow EDM (Enterprise Data Management) team members with your specialized knowledge in database management. Your insights will contribute to a more comprehensive understanding of data intricacies, enabling the team to make informed decisions.
- Chemical Data Maven: Become a subject matter expert in product data management. Your deep understanding of the nuances of product data will empower you to address queries, solve challenges, and provide strategic recommendations to improve our data management processes.
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