Statistician (contract)

Job type:
Start date:
Templeton and Partners
Published at:
flag_no Netherlands
Project ID:

This project has been archived and is not accepting more applications.
Browse open projects on our job board.

The Task:

Templeton and Partners Limited is currently working with a large commercial client in Amsterdam, we are looking for an experienced Statistician/Chemometrician for a long term project.

As Chemometrician/Statistician, you'll be leading wide-ranging statistical analysis of process data to help develop and deliver solutions for our downstream asset challenges, enabling insights that will ultimately improve the processes and drive performance.

In practice, that means you'll be part of a team designing statistical process control systems for fault detection and diagnosis and testing, as well as designing and implementing algorithms and methods.

Alongside your technical expertise, you'll also be calling on your natural people skills, confidently communicating business needs into data solutions, and presenting analytic results back into business language to a wide range of stakeholders, from scientists and engineers to industry managers in industry and academia.

You'll also need to be capable of managing multiple projects at the same time, and quickly learning new data analysis and chemometric techniques.


We're keen to hear from professionals with a strong background in Process Chemometrics and/or Applied Industrial Statistics, along with preferably a PhD in a relevant discipline, with some professional experience, or at least a Master's degree with some additional further experience.

  • Proficient in the use of chemometrics and multivariate statistical methods in non-linear/linear batch and continuous process data.
  • Proficient in Multivariate Statistical Process Control (MSPC): process data visualization, modelling and monitoring.
  • Experience in optimizing process conditions to maximize/minimize key process indicators or quality product properties using multivariate statistics and linear/non-linear optimization techniques.
  • Knowledge of design of experiments, general linear modelling, statistical modelling, and/or time series modelling.
  • An ability to work independently in MATLAB to implement, modify, adapt and apply MSPC methods to industrial data sets.
  • Expertise in chemometrics software, such as PLS toolbox by Eigenvector.
  • Proven industrial experience in applying MSPC to real process data in the form of current job or Post Doc experience.
  • Experience in the analysis of hyperspectral images and spectroscopic data would also be beneficial.