Microsoft Azure Edge + Platform (E+P) is a globally distributed team of engineers, architects, program managers, product managers, business program managers, business administrators, user experience researchers and designers who are responsible for the platform for Microsoft and for delivering Microsoft’s edge vision. We create the most reliable and trustworthy OS and platform services to empower Microsoft and our customers to achieve more. We unlock the next wave of opportunity at the edge through an at-scale ecosystem driving widespread adoption of our Microsoft cloud services.
Azure Edge + Platform engineering team is looking to hire talented and highly motivated Software Engineers to be on point for designing and implementing the next-generation Edge + Platform products and services for customers across the globe. This person will need to be proficient technically, with in-depth knowledge and experience in analyzing data and requirements, designing, developing and releasing services or products to end users.
We are looking for a Data Scientist who leverages understanding of data science and business to examine a project and consider factors that can influence final outcomes within a technical area. Understands where to acquire data necessary for successful completion of the project plan. Leverages knowledge of machine learning solutions. Understands linkage between achieved model and business objectives. Learns and understands the current state of the industry, including knowledge of tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance. Understands existing code to write efficient and readable code of their own for a specific feature, seeking guidance as needed. Develops understanding of data structures and their relationship to Microsoft's customer business. Leverages understanding of data science and business to examine projects through a customer-oriented focus.
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.
Responsibilities
As a Data Scientist, you will be responsible for the following:
Business Understanding and Impact
Leverages understanding of data science and business to examine a project and consider factors that can influence final outcomes within a technical area. Evaluates project plan for resources, risks, contingencies, requirements, assumptions, and constraints. 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. Explores data for key attributes and contributes to the development of data quality report describing results of the task, initial findings, and impact on the project. Collaborates with others to perform data-science experiments using established methodologies, statistics, optimization, and probability theory for general purpose software and statistical packages. Assesses different tools and techniques and selects the appropriate one. Serves as an effective partner in data preparation efforts to Solution Architects, Consultants, and Data Engineers. Adheres to Microsoft's privacy policy related to collecting and preparing data. Identifies data integrity problems.
Evaluating for Insight and Impact
Understands linkage between achieved model and business objectives. Assists with testing models on test applications and on real data or production data. Analyzes model performance. Incorporates implicit and explicit customer feedback into model evaluation. Conducts review of data analysis and modeling techniques to determine factors that may have been overlooked or need to be reexamined. Contributes to the summary of the review process.
Coding and Debugging
Understands existing code to write efficient and readable code of their own for a specific feature, seeking guidance as needed. Collaborates with other engineering teams to develop, test, and implement changes to optimize code to improve efficiency, reliability, diagnosability, maintainability, and operability of systems. Develops working expertise in proper debugging techniques such as locating, isolating, and resolving errors and/or defects. Collaborates with other engineers/project team members to integrate data models into customers' engineering systems. Understands big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, continuous integration and continuous delivery (CI/CD), Docker, Delta Lake, MLflow, AML, and representational state transfer (REST) application programming interface (API) consumption/development.
Industry and Research Knowledge / Opportunity Identification
Learns and understands the current state of the industry, 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. Attends internal research conferences and participates in on-hands training, when appropriate. Actively contributes to the body of thought leadership and intellectual property (IP) best practices.
Customer/Partner Orientation
Leverages understanding of data science and business to examine projects through a customer-oriented focus. Manages customer expectations regarding project/product progress and timeline. Takes responsibility to enhance customer excellence. Assists and learns from senior team members interpret results, develops insights, and communicates results to customers. Possesses basic understanding about model accuracy dependency on data quality and able to articulate it in customer discussions.
Business Management
Develops understanding of data structures and their relationship to Microsoft's customer business. Observes senior engineers and learns best practices in identifying growth opportunities, understanding strategy goals, customer- and product-strategy goals, and exploring opportunities for machine learning (ML) application, seeking guidance when needed. Understands business goals of the customer, per engagement basis.
Modeling and Statistical Analysis
Leverages knowledge of machine learning solutions (e.g., classification, regression, clustering, forecasting, natural language processing [NLP], image recognition) and individual algorithms (e.g., linear and logistic regression, k-means, gradient boosting, autoregressive integrated moving average [ARIMA], recurrent neutral networks [RNN], long short-term memory [LSTM] networks) to identify the best approach to complete objectives. Understands modeling techniques (e.g., dimensionality reduction, cross-validation, regularization, encoding, assembling, activation functions) and selects the correct approach to prepare data, train and optimize the model, and evaluate the output for statistical and business significance. Understands the risks of data leakage, the bias/variance tradeoff, methodological limitations, etc. Writes all necessary scripts in the appropriate language: T-SQL, U-SQL, KQL, Python, R, etc. Constructs hypotheses, designs controlled experiments, analyzes results using statistical tests, and communicates findings to business stakeholders. Effectively communicates with diverse audiences on data-quality issues and initiatives. Understands operational considerations of model deployment, such as performance, scalability, monitoring, maintenance, integration into engineering production system, stability. Develops operational models that run at scale through partnership with data engineering teams.
Embody our Culture & Values
Qualifications
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.
Other Requirements
Background Check: 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:
- Micosoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
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 $98,300 - $193,200 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 $127,200 - $208,800 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 for the role until August 27, 2024
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.