Overview :

MasterCard Advisors provides payments Consulting Services, Managed Services and Information Services to financial institutions, merchants and other industry verticals worldwide.

Advanced Analytics is charged with servicing Consulting Services, Information Services and Managed Services by centralizing and optimizing the world class analytical, modeling, software coding, data sourcing, product development, product management, econometrics, and associated delivery capabilities of the MasterCard Advisors organization.

Role :

Interface with multiple stakeholders and understand business requirements to engineer best-in-class solutions to deliver value for customers.

- Translate business requirements into tangible solution specifications and high quality, on time deliverables.

- Partner with different stakeholders and execute proof of concepts to assess the value of solutions.

- Analyze large volumes of transactional data to generate insights and actionable recommendations to drive business growth.

- Automate data analysis and insight generation with Python.

- Develop a detailed understanding of the Core objectives and strategies and how automation and machine learning can support each effort.

- Develop innovative and modern machine learning solutions.

- Passion for knowing for emerging trends and identifying relevant opportunities.

- Demonstrate ability to think strategically about business, product, and technical challenges

- Engineer machine learning solutions by leveraging one of world's largest data warehouse.

- Apply quality control, data validation, and cleansing processes to new and existing data sources.

- Support User Acceptance Testing for production applications; comply with all MasterCard internal policies and external regulations

- Support a high performance workplace

All about You :

- B.Tech. in a Computer Science, Information Technology, Engineering, or Mathematics. M.S. preferred.

- Strong experience with Python or R.

- Analytical/Problem Solving.

- Knowledge of database concepts.

- Knowledge of machine learning algorithms - Decision Tree, Clustering Algorithms and Linear Regression.

- Good to have experience in machine learning frameworks - TensorFlow, Scikit, Caffe and CNTK.

- Ability to work in fast paced and deadline-driven environment.

- Self-motivated with a proven track record of innovation and successful delivery.

- Relevant retail and payments industry experience a plus.

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