Data Scientist II

Overview

Do you want to be on the leading edge of using big data to drive engineering and product decisions for the biggest productivity software on the planet? Office Product Group ’s (OPG) mission is to delight our customers with compelling products and services. The Fundamentals User & Enterprise Lifecycle (Fuel) team is looking for an experienced professional with a passion for delivering business value with data insights and analytics to join our team as a Data & Applied Scientist. Specifically, you will be working on the Office Product Group Data Science team driving acquisition and monetization for Office apps (Word, Excel, and PowerPoint) across all platforms (client, web, mobile). Your work will directly drive growth in our consumer user base, both for paid subscribers and free users.

An ideal candidate should be an experienced data scientist with a proven track record of conducting complex data analysis, data mining, designing metrics/OKRs, OKR Tracking and experimentation in a real-world product setting. We want folks who are passionate about consumer products and driving user acquisition and growth. An ideal candidate will closely partner with product teams to drive product/business growth with meaningful insights and data-driven recommendations and experimentation. OPG product teams are very experimentation-driven and metric-driven, partnering closely with data science to help drive product success. Experience with experimentation and with driving growth in a subscription business is a plus.

Your primary responsibilities include understanding product/business priorities, conducting data analysis, defining product metrics, setting metric targets, tracking metrics, building data-driven hypothesis, participating in dashboard design, and running high-quality experiments to hit those targets. You will find and prioritize opportunities that you see and drive product investments. You will use the latest data analytics and data mining techniques to identify key product insights, work with product engineers to test and implement features or notifications that improve end user outcomes.  A successful candidate must tell clear and compelling stories, author documents, and make presentations to educate and inform the product teams and help shape the product and continuously improve our data-driven culture. 

Responsibilities

• Understand business/user problems. Identify and prioritize business opportunities, and clearly communicate insights and compelling data-driven stories.  
• Partners with product, research, and other data scientists to formulate data-driven answers to challenging business making problems, applying a wide variety of analytical techniques.
• Collaborate with software and data engineers to design metrics and reporting dashboards, participate in weekly scrum meetings, and ensure that the data and metrics are of high quality. You will be one of the primary - consumers of the dashboard to generate insights and hypothesis to drive growth.
• Partner with product teams to drive product impact via actionable hypothesis and experimentation.
• Identify and integrate multiple data sources, develop data expertise, apply data mining techniques to identify patterns and insights.
• Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis. 
• Transforms problems into analysis plans for data telemetry, metrics, data mining, reporting, and experimentation. Communicates and gets alignment on analytics priorities.
• Interprets results and develops insights with the proper business/user context.
• Communicates key outcomes with stakeholders and leadership.
• Acquires and uses broad knowledge of technical methods, algorithms, and tools, both internal to Microsoft and with the external scientific community.
• Knowledge of Machine learning techniques like Classification, Clustering, and Tree based algorithms is a plus.
• Validates, monitors, and drives continuous improvement to methods, and proposes enhancements to data sources that improve usability and results.

Qualifications

• M.S in Data Analytics, Data Science, Data Mining, Economics/Econometrics, Statistics, Operations Research, or a similar quantitative field  
• Solid foundational knowledge of data analytics, data mining, growth hacking and experimental design. 
• 5+ years' experience in an Analytics or Data Science role with focus on OKRs, Dashboards and Experimentation.
• 5+ years’ experience building product metrics and/or running AB experiments.
• 5+ years’ experience with statistical software and/or scripting languages (R, Python, Perl, SQL)
• 3+ years’ experience with statistical/ML algorithms for real world problems is a plus. 
• Deep understanding of big data systems, including map-reduce technologies like Hadoop/Spark.