Are you passionate about using data to shape up the next generation of online payments experience? Are you interested in uncovering business insights from big data? Are you a professional in performing data sciences to solve real world problems? If so, then we have a unique opportunity for you. Microsoft's C+E Business Operations Analytics team is looking for a data scientist who is passionate about online commerce and is looking to contribute enabling ecommerce capabilities for all of Microsoft's consumer and business online services such as Azure, Office 365, Bing, Dynamics, Microsoft Store, XBOX, Outlook and Windows Store, to just name a few. As Microsoft's online business rapidly grows, you have a unique opportunity to work on products that impact everyone on the planet.
We are an energetic, fast paced and exciting team. We analyze, optimize and implement models for a diverse range of problems for entire customers' online experience, ranging from customer purchase conversion, payment instrument selection, dynamic payment configuration, billing retry strategy optimization, to fraud anomaly detection and chargeback management. As a right candidate, you are a customer-focused, detail-oriented, results-driven analytic professional with great communication skills and a strong knowledge of predictive modeling and statistical techniques in the payments and fraud prevention space.
1. Graduate degree in Statistics, Operations Research, Machine Learning or other related fields and a minimum of 3 years' related work experience.
2. Proficiency in statistical, predictive modeling, machine learning with big data using tools like R, Python.
3. Experience in database record manipulation (mainly SQL) and big data solutions.
1. Proven ability and experience in using data science, statistical computing, and modeling to improve business KPIs.
2. Experience with optimization on state-of-the-art machine learning models.
3. Ability to write high quality production code for model deployment.
4. Solid grasp of A/B testing knowledge and extensive experience with hypothesis testing.
5. Strong understanding of ecommerce and payments systems.
6. Ability to be flexible enough to jump in and act as a team-member, taking immediate ownership of unanticipated scenarios, and responding to ad hoc requests requiring database skill to solve.
7. Demonstrated high energy/creativity, passionate for analyzing highly complex data sets, strong communication and project management skills.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Your responsibilities include:
1. Understand complex purchase and payment workflow in an ecommerce transaction system.
2. Manipulate large volumes of data, create new and improved techniques and/or solutions for data collection, management and usage.
3. Identify key metrics that determine the health of systems.
4. Use advanced statistical methods to unravel deep insights from large amounts of transaction and usage data.
5. Conduct experiments to gain insights into the business performance and recommend the right feature for production systems.
6. Build predictive models to optimize business processes for a best in class customer experience.
7. Closely work with business owners and engineering teams to deploy new features and predictive models into production.
8. Visualize and report on project results.
Microsoft is a technology company that develops and supports software, services, and devices.