Director of Analytics, Featurespace, North America

Visa•Atlanta, GA

20h•Hybrid

About The Position

We're looking for an outstanding leader for our North America Analytics team. Your future team produces industry leading machine learning models and decision systems whose actions protect hundreds of millions of cardholders and accountholders from fraud and financial crime every day across the North America Region. You'll lead an energetic group that thrive on achieving great customer outcomes every day. They are empowered to produce the best results for our customers and motivated by the opportunity to level up the fraud detection systems in the region. As Featurespace continues to grow worldwide, this position will see you significantly grow the high-performing Analytics team during an exciting period of expansion in the region. Away from leading the team and managing customer delivery work, you'll guide new commercial opportunities towards signature and contribute valuable insight towards the next generation of our fraud and financial crime prevention products. Our ideal candidate has built then deployed machine-learning models and complex data driven systems in fast moving environments, and well versed in the software engineering and ML Ops practices required to achieve this at scale. Beyond the technology, we're looking for someone who is comfortable consulting directly with customers to shape their problems into defined solutions and can gracefully lead and manage a team of managers and individuals. Day to Day It can be hard to know exactly what you'll be doing day to day from a job description that why we're telling exactly what the team you'll lead does! In a nutshell, we provide our customers with an analytics execution platform which responds in real-time to stop transaction and payment fraud in its tracks. The platform also has an important second function, it enables their fraud and risk operations teams to review high risk and suspicious activities identified by their analytics, orchestrate communication with their account and cardholders as well as reporting on the effectiveness of those analytics and operations. There are three key tasks for this Analytics team: System integration: No analytics execution platform is better than its data integration or customer specific configuration! Our Analytics team work closely with the customer during the system integration to ensure high-quality data is integrated and that the ARIC system is correctly configured to meet the fraud detection demands on the customer. Analytics and risk strategy consultancy. No analytics execution platform supplied by high-quality, clean data is better than the specific analytics that it runs! Our team work extremely closely with customer fraud and risk strategy teams to ensure that the analytics that our systems run produce industry-leading fraud detection outcomes. We do this by supporting and teaching our customers to use our system effectively but also lending our experience from across the industry and querying data sent to the platform to further optimise the analytics. Data science: Featurespace's machine learning models are one of the most attractive propositions to our customers! The final piece in the triad of team activities is the configuration of machine learning models from the rich datasets our customers possess. In this role, you will support your team through achieving outstanding results on behalf of our customers by: Managing the quality of output of the Analytics team, for North America Developing and coaching the team to have a culture of high performance, especially around quality of customer relationships, and constant and consistent experimentation to drive improvement Creating a regional team structure with good processes for all the major team functions where appropriate collaborating within the global Analytics function to establish these: recruitment, on-boarding, equipment requisition, learning and development, prioritization, knowledge sharing Providing the team a broader view of the business than just Analytics, understanding the perspective of customers and other departments and being able to influence external organizations This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Requirements

10 or more years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters/ MBA/JD/MD) or at least 3 years of work experience with a PhD
Ability to manage and prioritize personal workload.

Nice To Haves

12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD
Majority of your work is related to analytics/ business/ data science Subject matter expertise in the banking and payments industry.
A track record in developing future leaders from within your organization.
Experience managing geographically disperse or remote teams.
Ph.D. or other postgraduate level qualification with good mathematical background and knowledge of statistics Leadership of a talented and high-performing Analytics or Data Science team.
Passion for managing people and solving organizational challenges.
Willingness to share expertise to help grow the people the people around you.
Commitment to satisfying customer's requirements by producing class leading analytics.
Experience leading the deployment of machine learning models into high throughput, real-time prediction contexts.
Extensive commercial experience implementing statistical models and analytical algorithms in software.
Ability to lead system architecture/design discussions from an analytical and business impact perspective.
Strong, clear and concise written and verbal communication skills.

Responsibilities

Managing the quality of output of the Analytics team, for North America
Developing and coaching the team to have a culture of high performance, especially around quality of customer relationships, and constant and consistent experimentation to drive improvement
Creating a regional team structure with good processes for all the major team functions where appropriate collaborating within the global Analytics function to establish these: recruitment, on-boarding, equipment requisition, learning and development, prioritization, knowledge sharing
Providing the team a broader view of the business than just Analytics, understanding the perspective of customers and other departments and being able to influence external organizations