Senior Data Science Strategist - Featurespace

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

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.

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.

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• 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
  

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• Good degree in a scientific or numerate discipline, e.g. Computer Science, Physics, Mathematics, Engineering
  
• Excellent client facing skills, able to communicate complex analytical concepts to a variety of audiences, especially in a data science context. E.g. the application of practical machine learning algorithms to real-world data
  
• Ability to understand complex systems quickly
  
• Strong problem-solving skills (especially in data-centric applications) with motivation to take on novel and challenging problems
  
• Strong, clear, concise written and verbal communication skills
  
• Experience with software engineering practices, version control and the Unix -command line
  
• Strong technical and analytical skills with the ability and enthusiasm to pick up new technologies and concepts quickly
  
• Ability to manage and prioritise changeable workload ensuring internal and external deadlines are met
  
• Experience working with customers to gather complex sets of requirements including analytical system design, data integration design and model design
  
• Depth of experience in stakeholder management and managing customer expectations and common challenges
  
• Knowledge of Python and familiarity with complex SQL queries
  
• Industry experience in financial services, fraud and fraud strategy
  
• Experience in requirements management, business analysis or consulting environment
  
• Experience in delivery of enterprise software systems into large organisations either as vendor or customer
  
• Knowledge of fundamental machine learning concepts (feature engineering, algorithms, model evaluation, model bias)
  

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• Experience in deploying statistical models and analytical algorithms in industry
  
• Practical experience of the handling and mining of large, diverse, data sets
  
• Basic knowledge of event-driven systems and distributed computing for stateful systems
  
• Experience managing and developing high performing individuals
  
• Experience working with model governance bodies or awareness of the issues facing governance of machine learning models in production
  

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.