As a Senior Data Science Strategist you will work alongside data scientists 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.
Our EMEA team is based in Cambridge and London but work with customers across the entire region. For this role you will in line with Visa’s global policy ideally be comfortable coming into either the Cambridge or London office three times per week.
Day to day
We hire people with a willingness to adapt to a variable role, so along with the key responsibilities below, we ask for ownership of any other duties as required.
Lead 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, proactively anticipating any misalignment with statements of work or scope creep
Take the lead on internal and customer meetings where appropriate, handling questions confidently and pushing for key decisions from stakeholders
Drive interactions with customers to understand the problems they want to solve, proposing optimal analytical solutions in scoping and design phases
Educate customers on our platform and analytic solutions
Work with customers to understand the opportunities and constraints of their existing data in the context of our industry-leading analytical solutions
Proactively take steps to unblock deliveries and ensure timely deliveries, including but not limited to running additional workshops, holding meetings, and aligning stakeholders (internal and external)
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
Become expert in customer data structures and processes, route and translate information to internal development teams as required
Produce, review and quality control materials which feedback analytic results to customers (reports, presentations, visualisations)
Advise customer QA teams on the best strategies for effective analytical testing and support test phases
Lead customer Data Science and Analytics groups towards successful model development and deployment
Evaluate the analytical results on live systems and work with customers to suggest opportunities for improvement, and for enhancing and expanding existing solutions
Act as a trusted contact and analytics expert to Featurespace's highest profile accounts for queries relating to their analytics
Advocate for the customer when appropriate to engineering and product functions for enhancements to the analytic and product development roadmaps
Action team-wide improvements, continually providing feedback and insight to improve processes, and be heavily involved in leading internal change initiatives which enable internal teams to deliver more efficiently and effectively