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Data & Applied Scientist 12 views

Microsoft is looking for a data scientist to join the global payments and risk data science team within Cloud + AI to build the next generation data products to enable frictionless customer experience while minimizing payment fraud risk. If you are passionate about performing data science to solve real world problems, excited in applying machine learning to protect customers’ asset and combat fraud, energized by creating scalable analytics solutions that impact millions of customers, Microsoft has a unique opportunity for you.

Responsibilities

  • Research, define, and develop machine learning models and advanced analytics solutions to effectively detect payment fraud and other high-risk activities
  • Push boundaries of existing systems by creating new feature, algorithm enhancements and finetuning parameters
  • Collect and analyze complex dataset, study fraud patterns, and extract meaningful information to feed into risk models
  • Design and conduct experiments to gain insights into performance of new strategies and technologies
  • Establish scalable processes for large scale data analyses and model development
  • Partner with Product, Engineering, and Operations Teams on product requirement and delivery
  • Communicate verbally and in writing to stakeholders of various tech skillsets/knowledge to educate them on the systems, share insights and recommendations

Qualifications

  • Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related quantitative field
  • 5+ years of data science and ML development experience
  • Proficiency in creating and productizing high performance ML predictive models
  • Demonstrated ability in working with relational database using SQL

Preferred Qualifications

  • Track record of delivering end to end analytics solutions using data science, statistical computing, and predictive analysis on large scale data in the production environment
  • Experience in a data science specialization, including statistical data analysis, A/B testing in consumer-facing and/or enterprise applications
  • Strong coding skills in statistical or programing language (e.g., Python, R)
  • Hands-on experience using advanced data visualization to tell a story
  • Exemplary communication skills, ability to work with cross functional teams
  • Self-motivated, results driven and ability to self-start in a fast-paced environment

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