Microsoft Principal Data Scientist 

Australia, New South Wales, Sydney 

848162143

new solutionsa new technologyor solution is part of our work every day

broadly applicable

Data Scientistwith deep experience in data management and

Required Qualifications:

• Doctorate 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 statisticaltechniquesand reporting results)

• ORMaster's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statisticaltechniquesand reporting results)
• ORBachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statisticaltechniquesand reporting results)
• OR equivalent experience.

Preferred Qualifications;

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statisticaltechniquesand reporting results)

• ORMaster's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statisticaltechniquesand reporting results)
• ORBachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statisticaltechniquesand reporting results)
• OR equivalent experience.

• Experience working as part of geographically dispersed, diverse, and virtual teams
• Enjoy travel and are comfortable with travel up to 25%
• Demonstrated ability to work with customers and collaborate across company boundaries.
• 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

an informal and flexible work environment andbe welcome to work in the way that best enables you to get your job done

We invest in your health, wellness, and financial future by offering a competitive package including a wide range of benefits built around your personal needs and those close to you.

· Leverages subject matter expertise to analyze problems and issues facing projects to uncover, manage, and/or mitigate factors that can influence final outcomes across product lines. Partners with business team to drive strategy and recommend improvements. Raises opportunities to look for new work opportunities and different contexts to use existing work. Establishes, applies, and teaches standards and best practices.

Data Preparation and Understanding

· Oversees data acquisition efforts and ensures data is properly formatted and accurately described. Utilizes key technologies and tools necessary for data exploration (e.g., structured query language [SQL], Python). Uses querying, visualization, and reporting techniques to explore the data, including distribution of key attributes, relationships between attributes, simple aggregations, properties of significant sub-populations, and statistical analyses. Mentors and coaches engineers in data cleaning and analysis best practices. Identifies gaps in current data sets and drives onboarding of new data sets (e.g., bringing on third-party data sets). Drives discussions around ethics and privacy policies related to collecting and preparing data. Integrates industry-wide ethics insights and best practices to influence internal processes and drive decision-making. Builds data platforms from scratch across products. Builds data-science business solutions using existing technologies, products, and solutions, as well as established patterns and practices. Provides guidance on model operationalization of models created by data scientists. Identifies new opportunities from data and processes data in a way that is usable for general purpose. Actively contributes to the body

of thought leadership and intellectual property (IP) on best practices for data acquisition and understanding. Leads and resolves data-integrity problems.

Modeling and Statistical Analysis

Evaluating for Insight and Impact

· Conducts thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need reexamining. Utilizes results of the assessment and process review to decide on next steps (e.g., deployment, further iterations, new projects). Identifies new evaluation approaches and metrics and invents new methodologies to evaluate models.

· Tracks advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions. Researches and maintains deep knowledge of industry trends, technologies, and advances. Leverages knowledge of work being done on team to propose collaboration efforts. Proactively develops strategic responses to specific market strengths, weaknesses, opportunities, threats, and/or trends. Mentors and coaches less experienced engineers in data analysis best practices. Serves as a subject matter expert and role model for less experienced engineers. Identifies strategy opportunities. Actively contributes to the body of thought

leadership and intellectual property (IP) best practices by actively participating in external conferences.

Coding and Debugging

· Independently writes efficient, readable, extensible code/model that spans multiple features/solutions. Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement. Develops expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects. Leads a project team in the gathering, integrating, and interpreting of data/information from multiple sources in order to properly troubleshoot errors. Provides feedback on non-optimized features/solutions back to product group, and explores potential for new features. Leverages expert-level proficiency of 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.

· Embody our culture and values