Key responsibilities include:
- Manage and deliver analytics projects from conception to completion with actionable insights and recommendations
- Support project scoping, defining methodology, creating and executing on the framework with appropriate data mining techniques
- Support business development discussions on data science solutions, understand and gather client requirements and articulate clearly on solution frameworks
- Clearly communicate the findings and recommendations from analysis, drive deployment and implementation of analytics solutions, and track business value impact
- Independently develop and drive storyline with a clear so what and logical flow of insights and recommended actions for clients
- Work with VisaNet (i.e., Visa’s transaction data), clients and 3rd party data sources to create advanced data-driven solutions and dashboards
- Actively seek out opportunities to innovate by using non-traditional data and new modelling techniques fit for purpose to the needs of our clients
- Engage with external clients, and manage internal and external stakeholders
Qualifications
We are looking for a motivated, analytical minded individual with a track record of using data science and analytics expertise to unlock business value. A successful candidate should have accumulated a variety of experience, be curious about payments industry and application of data analytics, be results-driven and client-centric.
- Degree (Masters or higher would be an advantage) in IT, Computer Science, Data Science, AI, Machine Learning, Business Analytics or equivalent experience
- Minimum 5 years of professional experience in Data Analytics/ Data Science/ AI/ Machine Learning
- Deep analytical expertise in applying statistical solutions to business problems
- Experience with extracting and aggregating data from large data sets using SQL, Hive, Spark, or other tools
- Experience on programming languages (Python and/or C or more), ML/DL tools, Scikit-learn, Tensorflow or PyTorch and proficiency in one or more statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc
- Experience working with visualization tools such as Tableau and Power BI
- Demonstrated experience in managing multiple and concurrent projects with diverse cross-functional stakeholders
- Demonstrated ability to innovate solutions and solve business problems
- Strong internal team and external client stakeholder management with a collaborative, diplomatic, and flexible style able to work effectively in a matrixed organization
- Excellent presentation and storytelling skills, including strong oral and written capabilities