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You will be working in the department of Knowledge & Data Analysis
(KDA), a part of the Unilever Food and Health Research Institute in
Vlaardingen
(UFHRI), The Netherlands. The expertise of the KDA department (28 FTE's)
encompasses the translation of data (textual and numeric) into insights
and
is subdivided in four skills areas. In this role you will lead one of
these skills areas, Data Science, a team consisting of nine
statisticians. You
will report to the Department Director of KDA.
Skill Base Leader Statistics (Vacancy nr. 109584) PhD level statistician
with Industry track record.
Your role:
Ensuring high quality delivery of research and applied projects;
Acquisition/Initiation of new projects followed by effective resource
management; Leading the Data Science team, developing skills and
competencies; Deployment and development of new methods, bridging
academics and industry; Building and maintaining a network with the
academic community; Present and publish internally as well as
externally; Pro-active role as the statistics expert in
multi-disciplinary project teams; Member of the management team of KDA;
Assist and advise scientists in the Unilever R&D community on the use of
statistical methods for analyzing data.
Your background:
PhD in statistics, econometrics or mathematics; Minimum of 5 years
post-academic experience in (multidisciplinary) project management in
statistics or econometrics and a peer reviewed publication record;
Experience in leading a team; Preferred background in nutrition or
pharma industry, market research or econometrics (agencies), consultancy
(industry/academic) or psychometrics (academic); You are a strong team
leader with excellent communication and influencing skills; Fluent in
English.
Must have experience:
Experience in design and analysis of experiments, including power
analysis; Experience in regression modelling (linear, non-linear and
multivariate: MLR, PCR, PLS and others) and cluster analysis and
classification; Experience in using statistical software (SAS, JMP).
Preferred additional experience:
Optimal scaling methods / dual scaling (handling of categorical data);
Machine learning methods (Bagging-Boosting, Bootstrapping, CART, NNs,
SVM);
Bayesian statistics; Engineering methods (spline fitting, kalman filter,
fourier/laplace transformations); Application development in MatLab and
R.
To apply:
If you are interested in this challenging role and if you recognise
yourself in the above profile please send your CV and cover letter to
[log in to unmask] citing vacancy ref. 109584. This vacancy will
also be placed on the Unilever website on www.unilever.com/rdjobs.
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