Data Scientist

Microsoft is built on trust, and Azure is dedicated to becoming the most trusted cloud service for its customers. As Azure expands its services, certifications, and regions for its global customers, there is a growing need for increased support to uphold customer promises. The Azure Core Trusted Platform team is committed to enabling product teams to deliver capabilities that align with customer commitments and provide transparency.

We are looking for a Data Scientist with a proven track record of solving large, complex data analysis and machine learning problems in a real-world software product development setting. If you're a skilled engineer who is passionate about building end-to-end ML solutions and eager to learn new technologies, with the determination to solve complex technical problems, then this position is perfect for you.

Join our diverse and welcoming team that is dedicated to building privacy, security, and compliance engineering solutions for the Azure cloud. We use cutting-edge Azure service, data, and ML technologies to create products that are widely used across Microsoft teams. Our team values inclusiveness and diverse ideas, and we prioritize empathy, trust, and ownership to drive our team culture and deliver products quickly and iteratively. You'll work in a fast-paced environment, tackling problems that require creativity and collaboration to achieve meaningful business outcomes. We continuously strive for world-class engineering and operational excellence and encourage you to influence our designs and architectural roadmap and drive specific goals around scalability and availability. Join us and help make Azure the most trusted cloud platform! #AzureCoreTrustedPlatform

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.

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 tec
  • 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)
  • OR equivalent experience.
• 1+ year(s) customer-facing, project-delivery experience, professional services, and/or consulting experience.

Other Requirements:

• 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.

Additional/Preferred Qualifications: 

• 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.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $94,300 - $182,600 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $120,900 - $198,600 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

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.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

#Azurecorejobs

• Business understanding: Understands underlying business and product goals to inform design of data science solutions. Evaluates project plan for resources, risks, contingencies, requirements, assumptions, and constraints. Effectively communicates business goals, data insights, and data science solutions with variety of stakeholders.
• Data fluency: Explore, query, visualize, and process data sets to deeply understand available datasets. Evaluates and leverages existing methodologies and tools, such as statistical and ML packages. Able to identify and propose solutions to data integrity and quality issues.
• Modeling & analysis: Understands pros/cons of wide variety of ML techniques (classification, regression, clustering, time series analysis, natural language processing, etc.) and algorithms (linear/logistic regression, gradient boosting, agglomerative clustering, deep neural networks, Transformer networks, etc.) to select the most appropriate solution. Applies standard modeling techniques (cross-validation, regularization, ensembling, etc.) as appropriate to ensure high-quality, reproducible results. Conducts well-designed experiments, performs statistically sound analyses, communicates results clearly and accurately to stakeholders (engineering and PM teams and leadership).
• Measurement & iteration: Measures success of data science solutions in the context of business impact and goals. Analyzes model performance and quickly iterates to improve performance metrics.
• Engineering skills: Writes efficient, scalable, maintainable code. Performs comprehensive quality checks for data processing and ML modeling code. Understands proper debugging techniques when dealing with data pipelines and non-deterministic code. Familiar with big data tooling, ETL pipeline principles, REST API consumption and deployment.
• Customer focus: Considers user experience when designing data science solutions. Examine and evaluate projects through customer-focused lens. Responsive to user feedback.