The Opportunity
As aAnalytics Consultant, you will work alongside data scientists and risk strategy consultants, helping us deliver success on behalf of our customers by providing consulting expertise to customers on our advanced machine learning models and rules-based solutions that predict individual customer behaviours and prevent fraud and financial crime in real-time.
By combining data science fluency with a strong customer focus and consultancy mind-set, you will play a crucial role in ensuring that analytical requirements are properly understood; that optimal analytical solutions to the problems identified are delivered to end-to-end; and that – whether a large, multinational bank or a start-up fintech company – every customer is set up to succeed in fighting fraud and financial crime. The success of our customer projects will depend on you, and you will be the type of person who is excited by the responsibility this entails.
This is a hybrid role that can be based in either ourLondon or Cambridgeoffice, so you will ideally be comfortable coming into the office twice a week. Our EMEA team is based across both our London and Cambridge offices, but work with customers within the entire region. If you’re interested in the role but require more flexibility, please either discuss with the Talent team directly or outline your constrains in a cover letter alongside your application.
Day to Day
Support the end-to-end delivery of analytics, facilitating customers and internal teams in preparation for each stage Review and lock down project scope by understanding analytical requirements, identifying any misalignment with statements of work Drive interactions with customers to understand the problems they want to solve and proposing optimal analytical solutions Educate customers on ARIC, our fraud and financial crime detection platform, and our analytical solutions Work with customers to understand the opportunities and constraints of their existing data in the context of our industry-leading analytical solutions Advise and lead the customer through data readiness checks, while understanding common data issues and work with customers to resolve these efficiently Assist internal teams with the development and deployment of statistical models and algorithms for integration with Featurespace products Apply an understanding of the capabilities of the ARIC product and solutions in the analytics space Become an expert in customer data structures and processes as well as route and translate information to internal development teams as required Produce materials to feedback analytic results to customers, , in the form of reports, presentations, and visualisations Work with customer QA teams to advise on effective analytical testing and supporting test phases Support customer Data Science and Analytics groups with their model development and deployment in the ARIC platform Prepare for and run project workshops in the analytics and data space Evaluate the analytical results on live systems and work with customers to suggest opportunities for improvement where possible Provide analytic support and consultancy services to our customers
About you
Must haves:
Good degree in a scientific or numerate discipline, , in Computer Science, Physics, Mathematics, or Engineering Great client facing skills, and an ability to communicate complex analytical concepts to a variety of audiences, especially in a data science context, including on the application of practical machine learning algorithms to real-world data Ability to understand complex systems quickly Problem solving skills (especially in data-centric applications) Strong, clear, concise written and verbal communication skills Familiarity with software engineering practices, including version control and the Unix command line Experience working with customers to gather complex sets of requirements Experience in stakeholder management and managing customer expectations and common challenges Working knowledge of Python and experience writing SQL queries Knowledge of fundamental machine learning concepts (feature engineering, algorithms, model evaluation, model bias)
Great to haves:
Experience in requirements management, business analysis, and a consulting environment Experience developing statistical models and analytical algorithms Practical experience of the handling and mining of large, diverse, data sets Industry experience in financial services, particularly fraud and fraud strategy Basic knowledge of event-driven systems and distributed computing for stateful systems
Equal Opportunities
Here at Featurespace we are committed to being a place of equality, inclusion and respect to provide a safe environment for you to bring your authentic self to work. We know that we gain as much strength from our differences as we do our similarities. We value diversity and are dedicated to listening and learning from each other to build and maintain a positive and productive culture. We appreciate this will be an ever-evolving focus for the business to ensure everyone feels supported and has a sense of belonging.
