Data Scientist II

Microsoft

10d • Hybrid

About The Position

Come join us in the Azure Core Economics team, explore your passions, and impact the world! If you join the Azure Core Economics team, you will join a group of economists, data scientists, and software engineers within Azure Engineering that tackles a variety of data-intensive problems related to cloud economics that are of critical importance to Microsoft. Our team collaborates with many other teams in Microsoft on problems such as pricing, demand estimation and forecasting, commerce incentives, capacity management and planning, cost modeling, geo-expansion, fraud detection, yield management, virtual machine bin packing, and others.
As a Data Scientist II in the Azure Core Economics team, you will be responsible for leveraging large amounts of data to deliver products, prototypes, and actionable economic insights that drive improvements to Azure’s business. You will collaborate with colleagues in a wide range of disciplines on teams such as Azure Engineering, Business Planning, Capacity, Supply Chain & Provisioning, Finance, Microsoft Research, and the Office of the Chief Economist.

This opportunity will allow you to gain experience working on unique cutting-edge problems on the intersection of cloud computing, data science, economics, engineering, and research; develop deep expertise in economics, the cloud business, and a wide range of data science domains; and accelerate your career growth in an interdisciplinary environment. The team is supportive of flexible work, and candidates may work from home up to 2 days per week regardless of where they are located or as often as they would like if they have no collaborators in a Microsoft office within 50 miles of their residence.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Proficiency with relational databases and SQL, statistical packages in R, and standard libraries in Python
• Experience with distributed big data analytics (using, for example, Apache Spark, Hadoop, Azure Data Lake, or Cosmos)
• Solid understanding of and experience working with statistical inference techniques, machine learning models, and causal inference research designs.

Responsibilities

• Acquires data necessary for successful completion of project and utilizes querying, visualization, and reporting techniques to describe acquired data
• Understands existing code to write efficient and readable code for their own specific feature and collaborates with other engineering teams to integrate data models into engineering systems
• Understands modeling techniques and selects the correct approach to prepare data, train and optimize the model, and evaluate the output for statistical and business significance
• Assists with testing models on applications, real data, and production data, and analyzes model performance
• Assists in interpreting results, developing insights, and communicating results and insights to customers and stakeholders
• Engages with colleagues to understand strategy goals, explore opportunities for data science applications, and identify growth opportunities
• Learns and understands tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree