Short Description:
The Senior Manager in Data Science role at Visa in Bangalore demands expertise in risk analytics, machine learning, and payments. Responsibilities include leading cutting-edge risk analytics, collaborating with diverse teams, staying updated with tech, and managing data solutions for global impact. Applicants need 8+ years of ML experience, a quantitative post-grad degree, and comprehensive knowledge in risk management, payments, and AI-driven tools.
Location: Bangalore, India
Employment Type: Full-time
Company Overview
Visa is a global leader in digital payment services, facilitating over 215 billion payment transactions annually across more than 200 countries and territories. Our mission is to connect the world through innovative, convenient, secure, and reliable payment solutions, fostering the prosperity of individuals, businesses, and economies.
At Visa, we foster a culture of purpose, inclusivity, and personal growth. We believe in shaping economies that encompass everyone, leading to empowerment worldwide. Join us at Visa, where you can be part of a global network working for everyone.
Job Summary
We are currently looking for an experienced Senior Manager in Data Science to join our Central Europe, Middle East, and Africa (CEMEA) Data Science risk team. This role calls for a creative and analytical individual who can champion data-driven strategies within the region. As a Data Science Risk Manager, you will contribute to the development of predictive and prescriptive models, design contextual prototypes, and create impactful storyboards to promote data-driven strategies and solutions for Visa's clients. Your primary focus will revolve around credit, fraud, operational risks, deep risk analytics, risk scoring, and forecasting solutions.
Key Responsibilities
Develop and implement cutting-edge risk analytics solutions, encompassing both scoring and non-scoring models. Enhance data insights through effective visualization and storyboarding.
Collaborate with a diverse team, including Business Managers, Consultants, and Data Scientists from Visa and client organizations. Work together to strategize, co-create, deploy, and benefit from data-driven solutions.
Partner with regional and global Data Science teams to produce high-quality analytic products and solutions, contributing to Visa's growth in the region.
Stay at the forefront of Data Science technology by introducing innovative tools and techniques for generating valuable business insights.
Demonstrate the ability to quickly grasp and process unconventional data sources and platforms, developing advanced prediction algorithms based on artificial intelligence.
Pave the way for next-generation analytic methods to address business challenges when existing tools and techniques fall short.
Provide guidance and inspiration for junior team members in their analytical work.
Collaborate with internal Technology partners and Data Engineering teams to maximize the use of Visa's internal technology platforms, data, and the broader Visa ecosystem to fulfill our clients' technical data requirements.
Manage your own workload and that of your direct reports, offering guidance to streamline project flow and enhance process efficiency.
Foster the development and sharing of global best practices and knowledge management within the team.
Promote scalable and in-demand innovative ideas and approaches.
Advocate for internal requirements related to Model Risk Management, Visa Analytics Rules, and Global Privacy standards in client deliveries to uphold Visa's esteemed market position.
This is a hybrid position, allowing for a combination of remote and office work. Hybrid employees are expected to work from the office 2-3 set days a week, with an approximate guideline of being in the office at least 50% of the time, as determined by leadership and business needs.
Qualifications
Professional Experience
A minimum of 8 years of experience in applying Machine Learning solutions to solve business problems, including model development and production experience.
A post-graduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering.
Profound knowledge, experience, and understanding of quantitative techniques, particularly in Risk Management with a focus on Card and Payments, including familiarity with key Risk and Performance Indicators.
Experience in Card & Payments markets globally, with specific responsibilities in payments, retail banking, or retail merchant industries.
Solid comprehension of Payments and the Banking industry, covering card verticals such as consumer credit, consumer debit, prepaid, small business, commercial, and co-branded products.
Expertise in data, market intelligence, business intelligence, and AI-driven tools and technologies, with a proven ability to apply new techniques to solve business problems.
Proven track record in planning, organizing, and managing multiple large projects involving diverse cross-functional teams, including resource planning and delivery implementation.
Strong presentation skills, with the ability to tailor data-driven results to different audience levels.
Innovative thinking to develop 3rd party transaction Fraud models using deep learning and AI techniques.
Innovation of new products and solutions utilizing Visa's proprietary data, with scalability at a local and global level.
Building expertise in Risk advisory, creating next-generation risk engagement with Visa clients.
Collaboration with in-market VCA consultants and data scientists to deliver risk-related advisory engagements.
Establishment of an Intellectual Property (IP) risk repository for VCA by leveraging insights from consulting engagements, standardizing methods, creating a case study library, and templating modeling codes.
Collaboration with other Visa functions to capitalize on existing risk products/solutions and co-design new ones leveraging Visa's assets.
Demonstrated ability to deliver results within committed scope, timeline, and budget.
Strong project management skills and experience.
Willingness to travel within CEMEA on short notice.
Technical Expertise
Proficiency in distributed computing environments and big data platforms (e.g., Hadoop, Elasticsearch), as well as common database systems and value stores (e.g., SQL, Hive, HBase).
Strong understanding and experience with modern technology stack and microservice architecture, including Kotlin, Spring boot, PostgreSQL, Kafka, and AWS.
Relevant experience in handling unstructured/structured data from various sources such as Telco, Supermarkets, Social Media, Online logs, and E-commerce.
Capability to develop data pipelines (ETL, data preparation, data aggregation, and analysis) using tools like NiFi, Sqoop, Ab Initio, and familiarity with data lineage processes and schema management tools like Avro.
Proficient in various programming languages, including Python, R, Scala, Java, Matlab, C++, and SQL.
Experience in drafting solution architecture frameworks relying on APIs and micro-services.
Familiarity with common data modeling approaches and the ability to work with various data types, including JSON and XML.
Ability to build data pipelines (e.g., ETL, data preparation, data aggregation, and analysis) using tools such as NiFi, Sqoop, Ab Initio, with an understanding of data lineage processes and schema management tools like Avro.
Proficiency in various advanced data mining and statistical modeling techniques, including Predictive modeling, Classification techniques, Decision Tree techniques, and more.
Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling, Classification techniques, Decision Tree techniques, and more.
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