Mastercard works to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, their innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Their decency quotient, or DQ, drives culture and everything they do inside and outside of the company. Mastercard cultivates a culture of inclusion for all employees that respects their individual strengths, views, and experiences. They believe that their differences enable them to be a better team – one that makes better decisions, drives innovation and delivers better business results.
Job Title
Senior Data Scientist (London)
Who is Mastercard?
As a global technology company their mission at Mastercard is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, their innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Overview
International, Open Banking, Product Value Proposition Team is looking for a Senior Data Scientist to develop and drive forward Mastercard’s ambitious, data-driven open banking solutions, through the skillful application of data science and a highly customer centric focus. The ideal candidate is motivated, intellectually curious, technically excellent, a great communicator and someone who will enjoy helping us build out data science team and capabilities.
Role
As an individual contributor working within a growing data science team, you will take responsibility for developing market leading, innovative, analytical open banking solutions. Focused in the first instance on affordability/credit decisioning and identity/income verification use cases, you will help empower consumers and drive value creation across the client base.
Specifically In This Position, You Will
- In pursuit of highly valued, market leading, solutions and insights, apply a range of problem appropriate data science techniques to large data sets, from development to deployment support.
- Work closely with data engineers and developers to build and deploy interactive dashboards, providing the best, most engaging insights and UX for the clients.
- Communicate effectively with clients and stakeholders, ensuring their requirements are fully understood and met.
- Conduct effective customer trials to grow open banking impact, supporting data specification, data processing/analysis and result generation/presentation.
- Be highly proactive in pursuit of product excellence. For example, by investigating/proposing new data sources, encouraging cross team working, managing projects to agreed schedules and looking to utilise new tools and techniques.
- Help to develop, implement and honour effective, engaging team methods to support rapid prototyping, reproducibility, productivity, automation, and appropriate data governance.
- Engage with the wider Mastercard data science community, sharing best practice, knowledge, and insights, in support of collaborative, fulfilling work and value creation.
All About You
To succeed in this role, you will have:
- An undergraduate degree or higher in Computer Science, Data Science, Econometrics, Mathematics, Statistics, or similar field of study.
- Multi-project, hands-on experience of the end-to-end data science process in relation to large, complex data. From problem framing to results communication and solution deployment, you will be able to demonstrate having played a key part in a range of successfully delivered projects.
- Real world experience of developing and deploying interactive dashboards based on Plotly’s Dash framework or similar, alongside familiarity with business intelligence platforms such as PowerBI.
- Workplace Python coding experience, including a good knowledge of the principal Python Data Science / Machine Learning (ML) library ecosystem.
- Excellent written and oral communication skills for both technical & non-technical audiences.
To Succeed In This Role, You Will Be
- A highly engaged individual, evidenced through specific examples of collaboration, effective teamwork, successful independent work, and continued professional development.
Additionally, The Ideal Candidate Can Demonstrate
- Commercial, experience of successfully utilizing time series and natural language processing (NLP – especially in relation to topic modelling and named entity recognition) methods. A good working knowledge of supervised and un-supervised techniques is presumed.
- Practical knowledge/experience of solution deployment (data science pipelines, MLOps frameworks and libraries etc.).
- Experience of working in financial services with respect to consumer and/or business lending.
More Information
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1