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 Experience Organization (OXO) has embarked on a mission to delight our customers by using data informed engineering to develop compelling products and services. The FUEL team in OXO is looking for a Data Scientist with a passion for delivering business value and driving product improvements with predictive modeling, data mining, and experimentation. We are looking for a strong Data Scientist with 2+ years of experience with large, complex data analysis and machine learning problems in a real-world product development setting. Ideal candidates should be able to identify a business or engineering problem and translate it to a data science problem, identify and deeply understand potential data sources, conduct the appropriate analysis or modeling to reveal actionable insights, and partner with senior data scientists, program managers, and others to operationalize or drive decision making with their models. The Data Scientist will artfully explore and analyze the petabytes of client and service telemetry data, synthesize with other sources, collaborate with engineering leaders to formulate plans, and design metrics to measure performance and end-user impact via online experiments. He or she will leverage the latest in machine learning and predictive modeling techniques to identify and predict desired end-user outcomes, and work with product engineers to test and validate whether new features or communications drive the desired outcomes using our state-of-the-art, high throughput A/B testing platform. The successful candidate will have a proven track record of curiosity about data and the underlying application or business process, successful exploratory and explanatory data analysis, and the use of machine learning, predictive modeling, and/or statistical techniques to help drive decisions or provide value to the end-user via in-product or messaging applications. **Responsibilities** + Works with data engineers and data scientists to formulate data-driven answers to hard business and decision-making problems, applying a wide variety of data and techniques to help drive the engineering investments at a strategic and tactical level. + 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. Experience with Spark, Cosmos / Azure Data Lake, Kusto, SQL and/or other data manipulation techniques is required. + Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis. Able to work with junior data scientist to maximize impact and throughput while also mentoring and helping the team improve its overall data science skills and portfolio. + Develop measurements of end-user behaviors at various levels of aggregation, identify appropriate randomization units, aggregations, statistical measures for use in A/B tests and business metrics. + Interprets results and develops insights into formulated problems within the business/customer context and provides guidance on risks and limitations using data visualization and good writing skills to communicate findings. + Continually acquires and uses broad knowledge of innovative machine learning techniques, statistical inference, Bayesian analysis and other tools, is able to leverage techniques or tools developed by others in their organization or from the scientific literature and apply his or her own analysis of scalability and applicability to the formulated problem. + Validates, monitors, and drives continuous improvement to methods, and proposes enhancements to data sources that improve usability and results. **Qualifications** + Expert in one or more scripting languages like Perl, Python or SQL + 2 years plus of applying statistical modeling, machine learning and data mining algorithms to real world problems. + Deep understanding of big data systems including map reduce technologies like Hadoop and Spark + Expertise with data visualization and storytelling tools like R, Tableau or PowerBI, etc. + M.S or Ph.D. in Data Science, Economics/Econometrics, Statistics, Operations Research, Computer Science or similar quantitative field 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 at https://careers.microsoft.com/us/en/accommodationrequest . Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.