Analytics, Fraud & Risk - Managers & Senior Managers

Location: UK - London HQ. Type: Permanent. Salary: Negotiable . Reference# DH100121

Superb opportunity for an accomplished Senior Predictive Analytics Management Professional to join an exceptional Global Consultancy and be responsible for successful delivery of industry specific technology initiatives. Our client a global leader in their sector are currently looking to speak to Analytics Management Professionals with experience ranging from Manager to Senior Manager level.

Analytics enables their clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, they work with organizations to develop the analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition.

As part of their Analytics group, you will have the opportunity to work as part of a rapidly growing and dynamic global analytics team, driving significant business growth. You will have a primary focus on Fraud and Risk Analytics, supporting both project delivery as well as business development activities.

Responsibilities

Assessing opportunities and making subsequent recommendations as to the analytical approach
Support business development and demand generation activities for fraud & risk analytics across all industry groups, working in close collaboration with Industry Leads
Assume client-facing role that interprets and translates client requirements into a workable solution that delivers business benefits
Bring analytics insights and experience to shape the optimum solution for specific client needs
Act as Solution Architect for both opportunities and in-flight projects, including development of solution plan, estimates and delivery plan
Lead the delivery of analytics projects, providing supervision to more junior members of the team and enforcing best practise and quality standards
Contribute to innovative ideas and thought leadership; identify market gaps to help drive offering development
Responsible for building intellectual capital and supporting asset development for Fraud & Risk Analytics to differentiate the Analytics offerings to clients
Oversight of multiple consulting projects, involving mixed client project teams.
Modelling types may include linear/logistic regression, neural nets, decision trees, fractional factorials, etc.
Developing, testing, implementing, and potentially maintaining statistical modelling implementations
Interacting with clients of all levels to review expected outputs, applicability to business challenges, and model measurement
Guiding the data formulation process which may include identification of attributes, exploratory data analysis, data transformation, and temporal layout

Requirements

Deep Knowledge of Risk and Fraud analytics domains
Master’s in Statistics required (PhD is a plus)
7 – 15 years experience
The ability to develop solutions and value adding propositions and take these to market
Experience of managing, strengthening and broadening key client relationships
A proven track record in the development and implementation of data analytical models and solutions
Deep experience with data, visualisation, software tools and modelling techniques
Strong skills in Base SAS, SAS/STAT, and SAS Enterprise Miner, R, SPSS,
Familiarity with relational database design
Ability to work in a time-sensitive environment
Client management skills and experience
Exceptional interpersonal and presentation skills - ability to convey technology and business value propositions to senior stakeholders
Team oriented and collaborative working style, both with clients and those within the organization
Capacity to develop high impact thought leadership that articulates a forward thinking view of the market.
Demonstrated ability to develop younger talent and build a high performing team
Proficient in Microsoft Office (Word, PPT, Visio)
Strong communication skills (verbal and written)
Ability to work in a team environment or independently

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