As a member of SWIFT Financial Analytics team, you will be asked to work on a massive dataset using data science methodology to deliver value for management’s decision-making and strategy formation. This role will be ideal to Data Scientists or professionals with similar background, who are passionate about data. You should be able to manage and analyse large data sets with statistical and machine-learning methods, have a good understanding of supervised and unsupervised learning algorithms and strategies for data processing, data/text mining, and able to implement them in pragmatic business context. You are also expected to be self-motivated, able to work independently and at the same time collaborate well with the rest of the team.

What to Expect:
Develop strong business knowledge and acumen on SWIFT products and services.
Explore SWIFT data with the team to propose meaningful use cases, experiments, or projects.
Building statistical analysis and financial modelling techniques for company budgeting and forecasting purposes.
Analyzing product usage and customer behaviour to drive recommendations for improved customer experience across business units.
Develop models to detect anomaly or special patterns in SWIFT data as an alert system for changing business evolution.
Develop efficient financial simulation model for product pricing, cost, profitability in line with the company strategy.
Design and build high-performance identity verification applications to detect fraud cases.
Lead projects end-to-end which involves cross-functional collaboration, timely and effective communication, and delivering interpret able results which is meaningful to business.
Promote data driven culture by shaping future data needs/models and improve financial forecasting activities within the team.
Implement continuous improvements to work process and models.
Maintain adequate and structured documentations for all business processes within team.




What will make you successful:
Bachelor’s Degree in Data Science, Econometrics, Engineering, Mathematics, Applied Science, Computer Science, Statistics, Physics, or comparable field. Candidate with Master’s qualifications or research experience is a strong plus.
Excellent verbal and written communications in English
2-5 years of experience in data science/analytics with a strong background in one or more areas: time-series forecasting, anomaly detection, recommender system, fraud detection.
Knowledge in using integrated AI platform : KNIME, C3 AI, DataRobot
Adept in multiple programming languages : primarily Python (generic, Numpy, Pandas), R, and SQL.
Familiar with data visualization stack: Tableau, Microstrategy, PowerBI, matplotlib.

Educational level:

Bachelor’s Degree

Level of experience (years):

Mid Career (2+ years of experience)

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