Senior Data Scientist

Do you want to be on the leading edge of using big data and help drive engineering and product decisions for the biggest productivity software in the planet? Office Product Group (OPG) has embarked on a mission to delight our customers by using data-informed engineering to develop compelling products and services. OPG is looking for an experienced professional with a passion for delivering business value with data insights and analytics to join our team as a Senior Data Scientist. 

We're the ones obsessing over enterprise customers, making sure their experiences with our products are top notch. Our core mission is keeping customers “healthy” – this involves not only driving performance and coordinating tenant-centric health efforts across OPG, but also ensuring our customers are on the latest, fastest, most productive, and best versions of the incredible apps that make up Office. To fulfill this mission, we are looking for an individual who joins us to drive and deliver core Performance improvements constantly, across the suite, leading to delightful experiences for all users.  

We are looking for a strong 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. Ideal candidates should be able to take a business or engineering problem from a PM or Engineering leader and translate it to a data science problem. This includes all the steps to identify and deeply understand potential data sources, conduct the appropriate analysis or modeling to reveal actionable insights, and then work with data or AI engineers to operationalize the metrics or solution.  

You will be delivering results through innovation and persistence when similar candidates have given up.

Qualifications 

• 6+ years of experience involving software design and programming experience with languages like C/C++/C#/Java/Python required and hands on experience developing applications in the cloud using technologies such as SQL, Kusto, Databricks, Azure ML, Spark etc.   

• Candidate must be able to communicate complex ideas and concepts to leadership and deliver results.   

• Candidate must be comfortable in manipulating and analyzing complex, high dimensional data from varying sources to solve difficult problems.   

• Bachelors or higher degrees in Computer Science, Statistics, Mathematics, Physics, Engineering, or related disciplines. 

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. 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.

Responsibilities 

• Identifies data sources, integrates multiple sources or types of data, and develops expertise with multiple data sources to tell a story and to compensate for missing data, identify new patterns and business opportunities, and communicate visually and verbally with clear and compelling data-driven stories.   

• Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis.  Able to work with, leverage and mentor other data scientists to maximize impact and throughput while also mentoring and helping the team improve its overall data science skills and portfolio.   

• Transforms formulated problems into implementation plans to develop risk models to predict customer churn by designing and applying appropriate decision-making metrics, backed up with thorough exploratory data analysis, and ensuring the decision criteria for the experiment are correctly reported and interpreted in light of the statistical confidence.   

• Interprets results and develops insights into formulated problems within the business/customer context and provides guidance on risks and limitations.   

• Acquires and uses broad knowledge of innovative methods, algorithms, and tools from within Microsoft and from the scientific literature and applies his or her own analysis of scalability and applicability to the formulated problem.