Data Analyst with spectroscopy background

HybridMidData Analystposted 2mo ago

✦Role summaryAI-generated

The role involves applying spectroscopy and chemometric techniques to monitor and maintain authentication models while collaborating with data scientists in a regulated environment. Candidates will use Python tools such as Jupyter, NumPy, and scikit-learn to develop, validate, and document multivariate models.

Skills required

Spectroscopy Nir Chemometrics Multivariate analysis Pca Pls-da Python scikit-learn Data analysis NumPy SciPy Data science

About this role

We are looking for a Data Analyst with expertise in spectroscopy (NIR required), chemometrics, and multivariate data analysis to support the monitoring, validation, and maintenance of authentication models, working closely with Data Scientists in a regulated environment.

Requirements

Strong background in spectroscopy and chemometrics (NIR mandatory; Raman / FTIR as a plus)
Proven experience in multivariate analysis and chemometric modelling (PCA, PLS‑DA, classification models)
Ability to monitor, interpret, and maintain model performance across spectral libraries
Hands‑on experience with ideally Python‑based data analysis (e.g. Jupyter notebooks, NumPy, SciPy, scikit‑learn)
Experience working with validated / regulated environments and producing inspection‑ready documentation
Candidates must declare criminal record extract not older than three months

Key Responsibilities (scope‑focused):

Interpret and monitor performance of authentication models within the spectral library
Support creation and review of model snapshots, including associated metadata checks
Collaborate closely with Data Scientists and technical teams on model refinement and updates
Contribute to model validation, release, and maintenance in support of Authentifield operations
Document methods, decisions, and changes in line with governance and compliance expectations
Data Science team coordination