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Sr Manager Data Science

Visa

Dubai

Hybrid

AED 120,000 - 200,000

Full time

Today
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Job summary

A global payments technology company is seeking a Senior Data Scientist to lead data-driven innovations in the payments and cards domain. The ideal candidate will have over 10 years of experience in machine learning and data analytics, a postgraduate degree in a quantitative field, and strong programming skills. This hybrid role involves working closely with cross-functional teams to develop cutting-edge analytic solutions and commercialize existing assets, ensuring Visa maintains its technological leadership in the industry.

Qualifications

  • Minimum of 10 years in Machine Learning solutions and model development.
  • Expertise in distributed computing and big data platforms.
  • Strong ability in multiple programming languages.

Responsibilities

  • Identify innovation opportunities in data processes.
  • Collaborate with cross-functional teams on data-driven solutions.
  • Drive commercialization of existing models and solutions.

Skills

Machine Learning expertise
Analytical solutions commercialization
Strong programming skills in Python and SQL
Project management abilities

Education

Postgraduate degree in a quantitative field

Tools

Hadoop
Elasticsearch
Job description
Principle Responsibilities & Key Results Area
  • Identify innovation opportunities around data and data‑related processes that will help our clients implement fact‑based decisioning processes within their cards and payments program.
  • Work entails heavy focus on transaction data modelling and analytics for cards and payments products. Work with a broader team that consists of Business Managers, Consultants and Data Scientists from both Visa and client organizations to strategy co‑create, deploy and reap the benefits of data‑driven solutions.
  • Work with regional and global Data Science teams to develop high‑quality analytic products and solutions that promote Visa's growth in the region.
  • Focus on creating scalable framework for Gen AI ML models.
  • Keep Visa at the forefront of technological advancement in Data Science by introducing cutting‑edge tools and techniques for generating business insights.
  • Develop next‑generation analytic methods where existing tools and techniques are inadequate to address business challenges.
  • Drive commercialization of existing scalable assets (models, dashboards, solutions).
  • Collaborate with internal Technology partners 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.
  • Develop share and build global best practices and knowledge management within the team.
  • Socialize innovative ideas and approaches that are scalable and have market demand.
  • Champion internal requirements around Model Risk Management, Visa Analytics Rules and Global Privacy standards around client delivery to ensure that Visa's highly regarded market standing is maintained.
  • Work closely with Data Engineering DS teams and vendors; communicate the business stakeholders' needs and ensure the development team delivers within established acceptance criteria including expected quality and performance.
  • Drive strong collaboration with VCA CEMEA Service Line Leads (Portfolio Management, Digital Risk, Merchant & Acquiring Commercial) understanding the market landscape and demand, identification of potential opportunities for scalable solutions, collecting business requirements and supporting in market enablement and GotoMarket.
  • Work with Global Practice Leads to incorporate best practice source analytical or other services and leverage global consulting solutions.
  • Deliver and manage a network of external Vendor or agency partners. Maintain excellent relationship with vendor team at large, supervising deliveries as needed. Assist in selecting, recruiting, inducting and onboarding of vendors. Work with other teams and external consultants to develop new and improved tools and techniques for future Consulting activities.
  • Manage the project budget and resources to perform all required duties.
  • Liaise with VISA functional teams Finance, Audit, Legal, Tax, Sourcing to define and implement processes to optimize the daily engagement of vendors and the relationships with clients.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

Key Competencies

  • Minimum of 10 years of expertise in applying Machine Learning solutions to business problems, model development and production experience required.
  • Experience of using GenAI to solve business challenges.
  • Postgraduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics or Engineering.
  • Experience working in one or more of the Card & Payments markets around the globe with specific responsibilities in payments, retail banking or retail merchant industries.
  • Good 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 demonstrated ability to incorporate new techniques to solve business problems.
  • Proven track record in commercializing analytical solutions.
  • Experience planning, organising and managing multiple large projects with diverse cross‑functional teams including resource planning and delivery implementation; experience in presenting ideas and analysis to stakeholders whilst tailoring data‑driven results to various audience levels.
  • Proven ability to deliver results within committed scope, timeline and budget.
  • Very strong people/project management skills and experience.
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.).
  • Familiarity with both common computing environments (e.g. Linux, Shell Scripting) and commonly used IDEs (Jupyter Notebooks).
  • Strong programming ability in different programming languages such as Python, R, Scala and SQL.
  • Experience in drafting solution architecture frameworks that rely on APIs and microservices.
  • 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, etc.
  • Expert knowledge of advanced data mining and statistical modelling techniques including Predictive modelling (e.g. binomial and multinomial regression, ANOVA), Classification techniques (e.g. clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g. CART, CHAID).
Leadership Competencies
  • Demonstrates integrity, maturity and a constructive approach to business challenges.
  • Serves as a role model for the organization by implementing core Visa Values.
  • Strives for excellence and extraordinary results.
  • Uses sound insights and judgments to make informed decisions in line with business strategy and needs.
  • Able to allocate tasks and resources across multiple lines of businesses and geographies.
  • Able to influence senior management both within and outside Data Science.
  • Successfully persuading internal stakeholders to commit to best‑in‑class solutions when required.
  • Leverages change management leadership as required.
  • Fluency in English is mandatory.
Additional Information

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.

Remote Work

No

Employment Type

Fulltime

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