Senior Manager - Data Science

Company Description

Visa is a global leader in digital payments, conducting more than 215 billion payment transactions between consumers, merchants, financial institutions, and government entities across over 200 countries and territories annually. Our mission is to link the world through the most advanced, convenient, reliable and secure payments network, allowing individuals, businesses, and economies to prosper.

By joining Visa, you become part of a culture of purpose and belonging – where your growth is a priority, your identity is embraced, and your work matters. We believe that economies that include everyone, uplift everyone. The work you do will direct impact billions of individuals worldwide, helping to unlock financial access and enable the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

The Sr Manager of Data Science is key risk role in the Central Europe, Middle East and Africa (CEMEA) Data Science risk team. We are looking for an innovative and analytical individual to drive our data-centric strategies within the region. As a Data Science Risk Manager, you'll take part in creating predictive and prescriptive models, and developing context-based prototypes and impactful storyboards that promote data-driven strategies and solutions for Visa clients. The role will mainly focus on engagements in the areas of credit, fraud and operational risks, deep risk analytics, risk scoring, and forecasting solutions.

Principal Responsibilities

• Work involves a heavy emphasis on developing and implementing top tier risk analytic solutions, including scoring and non-scoring models. Develop and deliver powerful insights from data through superior visualization and storyboarding

• Cooperatively work with a wider team composed of Business Managers, Consultants, and Data Scientists from both Visa and client organizations to strategize, co-develop, implement and reap the benefits of data-driven solutions

• Collaborate with regional and global Data Science teams to create high-quality analytic products and solutions that promote Visa’s growth in the region

• Keep Visa at the vanguard of technological advancement in Data Science by introducing state-of-the-art tools and techniques for generating business insights

• Capability to quickly understand and process alternate/non-traditional data sources/platforms and develop AI-based advanced prediction algorithms

• Develop next-generation analytic methods where existing tools and techniques are insufficient to address business challenges

• Review, guide, and inspire the analytical work of junior members in the team

• Partner with internal Technology associates and Data Engineering function to best leverage Visa’s internal technology platforms, data, and the broader Visa ecosystem to support our clients’ technical data needs

• Manage workload for oneself and any direct reports, providing prioritization guidance for project flow to improve process efficiency

• Develop, share and build global best practices and knowledge management within the team

• Propagate innovative ideas and approaches that are scalable and have market demand

• Spearhead internal requirements surrounding Model Risk Management, Visa Analytics Rules, and Global Privacy standards related to client delivery to ensure Visa’s highly esteemed market standing is maintained

This is a hybrid role. Employees in hybrid roles can divide their time between both remote and office work. They are expected to be in the office for 2-3 fixed days per week (determined by leadership/site), aiming for a split of being in the office 50% or more of the time based on business needs.

Qualifications

Professional Experience
• Minimum of 8 years of expertise in applying Machine Learning solutions to business problems – model development and production experience required
• Post-graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering
• Exceptional knowledge, experience and understanding of quantitative techniques (modelling, statistics, root-cause, etc.) applied to Risk Management with a focus on Card and Payments. Familiarity with key Risk and Performance Indicators. Experience working in one or more of the Card & Payments markets globally, with specific responsibilities in payments, retail banking, or retail merchant industries
• Solid understanding of Payments and the Banking industry, including card verticals such as consumer credit, consumer debit, prepaid, small business, commercial and co-branded product
• Expert knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies, with proven ability to incorporate new techniques to solve business problems
• Experience planning, organizing, and managing multiple large projects with various cross-functional teams, including resource planning and delivery implementation
• Experience presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels
• Develop and innovate 3rd party transaction Fraud models using deep learning and AI techniques
• Create novel products/solutions using Visa's proprietary data that can be scaled both locally and globally
• Build Risk advisory related knowledge and capabilities creating next-generation risk engagement with Visa clients
• Collaborate with in-market VCA consultants and data scientists to deliver risk-related advisory engagements
• Establish Intellectual Property (IP) risk repository for VCA by capitalizing on learnings from consulting engagements (e.g., constructing standard methods, creating a library of case studies, templating modeling codes)
• Reengineer and/or package risk consulting methodologies and data-driven solutions as appropriate, ensuring world-class best practices and efficiency through economies of scale
• Collaborate with other Visa functions (e.g., Risk, Products) to leverage existing risk products/solutions and co-design new ones using Visa’s assets (expertise, data, capabilities)
• Proven ability to deliver results within committed scope, timeline and budget
• Exceptionally strong project management skills and experience
• Willingness to travel within CEMEA at short notice
Technical Expertise
• Expertise in distributed computing environments/big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.)
• Deep understanding and experience of modern technology stack and microservice architecture including Kotlin, Spring boot, PostgreSQL, Kafka, AWS
• Relevant experience of engineering unstructured/structured data from Telco, Supermarket, Social Media, Online logs, E-commerce, etc is preferable
• Ability to write MapReduce jobs from scratch and fluency with Spark frameworks
• Familiarity with common computing environments (e.g., Linux, Shell Scripting) and widely used IDE’s (Jupyter Notebooks), proficiency in SAS technologies and techniques is preferred
• Strong programming skills in various programming languages such as Python, R, Scala, Java, Matlab, C++, and SQL
• Experience in drafting solution architecture frameworks that rely on APIs and micro-services
• Familiarity with common data modeling approaches and ability to work with various datatypes including JSON, XML, etc.
• Ability to build data pipelines (e.g., ETL, data preparation, data aggregation and analysis) using tools such as NiFi, Sqoop, Ab Initio, familiarity with data lineage processes and schema management tools such as Avro
• Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain Monte Carlo, Gibbs Sampling, Evolutionary Algorithms (e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks, Bagging and Boosting algorithms, etc.
• Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA), Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g., CART, CHAID)

Additional Information

Visa is an EEO Employer. Qualified candidates will receive consideration for employment regardless of race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified candidates with a criminal history in a way that is consistent with EEOC guidelines and pertinent local law.