Statistical Modelling Manager

Location: Amsterdam, Noord-Holland
Salary: Bespreekbaar
Posted: 18 days ago
Contract Type: Permanent
Industry: Data Analytics & Quantitative
Contact Name: Reinier Hovius
Contact Email:

Reinier Hovius

Managing Consultant, Netherlands

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Statistical Modelling Manager

About the organization:

This multinational organization is opening his doors in Amsterdam as of January 2019. The organization is predominantly focused on understanding, measuring, and predicting consumer financial behaviour. Their Amsterdam subsidiary will be dedicated to advanced analytics that support the organizations core operating geographies (the UK, DACH, and Nordic regions). Starting with a team of 7, it aims to grow to 25 professionals by the end of 2020.

As part of a thriving, pan-European analytic community, this role is an exciting opportunity to join a team that partners broadly within the organisation and influences the company's operational, analytic, and financial strategies.

Key responsibilities

* As a practitioner-manager, build, enhance, and maintain predictive models focused on consumer segmentation, activity/effort prioritization, forecasting, and operational performance enhancement using the most appropriate statistical and machine learning methodologies

* Build, develop, and manage a high performance team through direct coaching and mentorship, and guide teammates to reach further and achieve more

* Provide analytic leadership within the Lowell community to include (a) general statistical expertise, (b) project leadership, especially involving complex problem solving, and (c) identifying new opportunities to use predictive modelling in pursuit of revenue and cost targets

* Research and development activities focused on sociodemographic analyses, subprime credit consumer dynamics, and financial distress

* Translate unstructured business problems into well-defined and tractable modelling projects

* Develop short presentations and memoranda to communicate key messages and findings to senior leaders and colleagues

* Work closely with partners and stakeholder groups (including operations, other staff functions, and adjacent teams within Decision Science) to provide direct support and accomplish shared goals

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