Microsoft Data Scientist 

United States 

820123245

Required Qualifications

• 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.

Preferred Qualifications

• 5+ years of hands-on experience with data science, engineering, and analytics tools
• Experience working with large, distributed data sets to derive actional insight
• Advanced skills in big data programming language
• Advanced skills and experience in Power BI, PowerApps, Kusto, R and/or Python
• Solid understanding of statistical analysis framework and machine learning algorithms
• Interpersonal communication and ability to leverage the data to tell a story
• Collaboration and program management skills
• Ability to work cross-functionally, building and maintaining trust with internal stakeholder

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: .

Microsoft will accept applications for the role until July 9, 2024.

Business understanding and Impact

• Leverages understanding of data science and business to examine a project and consider factors that can influence final outcomes. Documents key business objectives. Effectively communicates business goals in analytical and technical terms. Consistently shares insights with stakeholders.

Data Preparation and Understanding

• Understands where to acquire data necessary for successful completion of the project plan. Utilizes querying, visualization, and reporting techniques to describe acquired data, including format, quantity, identities, and other surface properties. Collaborates with others to perform data-science experiments using established methodologies, statistics, optimization, and probability theory for general purpose software and statistical packages. Serves as an effective partner in data preparation efforts to Solution Architects and other business stakeholders (Commercial Solution Areas). Adheres to Microsoft's privacy policy related to collecting and preparing data. Identifies data integrity problems.

Develop and implement data science solutions that drive actionable insights for the business

• Collaborate with stakeholders to design and deliver tailored reporting, analysis, and modeling solutions that address specific business needs. Utilize advanced knowledge in data science, coupled with a solid understanding of business contexts, to evaluate and integrate the latest technologies in reporting, statistical analysis, and machine learning.

Business and Research Knowledge/Opportunity Identification

• Learns and understands the current state of the Commercials Solution Areas business, including knowledge of tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance. Maintains knowledge of current trends within the discipline.

Other

• Be a hands-on technical lead who can own, drive, and develop insights from conception to release.
• Be curious and willing to continuously learn about the business. Partner with stakeholders to define the critical insights required to make informed business decisions and sales precision. Continuously evolve the output of this role and ensure business alignment and impact.
• Learn and understand a broad range of data resources and know when, how, and which to use and which not to at any given time.
• Demonstrated analytical problem solving with adaptability to manage through ambiguity.
• Collaboration skills that promote a positive team environment by modeling behavior of continuous learning.
• Ability to manipulate and analyze complex, high-volume, high-dimensionality data from various sources.
• Evaluate, adapt, and apply advanced data science techniques, including statistical analysis, machine learning, and causal inference, to develop and deliver high-quality and actionable solutions.
• Design, build, and maintain all business reporting and dashboards, ensure data integrity and accuracy.

• Embody our