Develop, maintain and enhance analytical methodology that delivers customer-level insight
Apply the analytical framework and analysis to drive key business and customer strategy decisions
Manage the maintenance of existing segmentation / profiling analysis and the development of propensity models to guide customer retention / engagement and ARPU development strategies
Play an active role in proposing new approaches, methodologies and recommendations.
Develop an Analytics Practice in order to create and maintain a repository of knowledge and portable SAS scripts within the team
Provide best practices training in analytics and advanced SAS coding techniques
Create advanced SAS macros that encapsulate new methodology / IP created within the team, and which can be deployed across multiple projects in a repeatable fashion
Deep insight on the impact and measurement of the key Loyalty and Customer Base Management services ensuring implications of analytical findings are correctly presented and explained in a timely manner.
Proactively approach Business Departments offering new insights and proposing ways to action them
Act as the day-to-day main point of contact for analytical queries coming from the accounts supported.
Presentation of modeling / analysis results to a non-technical audience both internally and externally.
Provide performance measurement and insights into key business drivers.
Key Performance Measures:
Creation of a process to capture, document and disseminate existing / new methodologies created within the team
Amount of training sessions conducted
Quality and depth of insight delivered
Quality and quantity of actionable recommendations offered around targeted customer treatments
On-time delivery of analysis
Customer satisfaction of internal and external stakeholders. Development of relationship with stakeholders
Relevant experience of 7-10 years in a similar customer analytics and modeling role ideally gained within a commercial B2B environment.
Experience of CRM/Customer Insight profiling, segmentation and propensity modeling with manipulation of large datasets is also essential.
Degree educated in Statistics, Mathematics, Information Technology or Engineering. Statistically literate.
Deep knowledge of predictive modelling and sophisticated analytic techniques (e.g. regression, clustering, decision tress, etc.)
Technical Skills: Highly numerate with strong analytical skills. SAS Base, SAS Stat, SAS Macro. SQL querying. Web Analytics Tools. Strong Access and Excel skills.
In-depth knowledge of SAS Application design/development/testing methodologies, techniques and tools.
Business acumen apply business awareness to data interpretation. Curious about strategic information hidden behind data. Critical attitude towards data knowledge of data quality and data mapping issues.
Demonstrate the necessity to have accurate data and ability to understand complex data flows and identify possible areas of data corruption, inadequacies, etc.
Ability to define data requirements, identify key validation areas and demonstrate integrity of data to be used for modelling / segmentation
Ability to handle different data sources and define efficient / automated ETL processes for combining these
Strong work ethic focused on providing excellent customer service.
Excellent communication and influencing skills with the ability to present information.
Customer Relationship Management / customer loyalty experience.
Fluency in English is a requirement, foreign language capability is desirable.
Pan European (or at least multi-country) experience beneficial
A candidate with the ability to build the reputation of Lumata by challenging current thinking and becoming a trusted impartial counsel.
Able to work to a very high standard even under pressure and tight deadlines. Organizationally aware knowledge of the best ways to get things done. Great attention to detail.
Passionate about work. Enthusiastic takes pride in performing own job to the highest standard