The Consumer Communications & Communities team is looking to hire a data scientist. Do you have a passion for using data to help build great consumer products? If so, we are looking for folks like you who love building high-quality products and embrace agile experimentation and helping the teams be data inspired. 

We’re working on Microsoft Teams Consumer – a consumer messaging & productivity product to bring groups of people together to call, chat, meet, and get things done —all in one app. Our team is at a crucial point in our journey where data can have an outsized impact. We have a lot of interesting problems to solve as we work towards our mission to “Empower every person and organization to achieve more by helping them build meaningful connections with the people and communities that matter most”. 

We have a large engineering team is Prague and IDC and are looking for folks that can work in those time zones. 

Your colleagues will be among the best in the industry - they’ve earned their stripes in startups and v1 products and share an intense passion for delivering an amazing product. 

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

• Measurement: Define, invent, and deliver metrics which accurately measure the quality of online information, and the satisfaction/success of our customers. 
• Models: Develop ML/Statistical models to measure/predict the quality of online content and/or user interactions with large scale AI systems. 
• Experimental Design: Think critically about sampling and experimental design. Developing innovative strategies and products in these areas. 
• Product Iteration: Interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve. 
• Strategy: Translate strategy into plans that are clear and measurable, with progress shared out monthly to stakeholders. 
• Cooperation: Partner effectively with product management, engineers, and other areas of the business. 
• Influence: engage with stakeholders to produce clear, compelling, and actionable insights and data-science driven workflows that influence product and service improvements. 

Qualifications

Required Qualifications: 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 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 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 data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• Customer-facing, project-delivery experience, professional services, and/or consulting experience.
• Experience in data science modeling, statistics, analytics, business intelligence, or data-driven business strategy. 
• Solid hands-on skills in SQL, and R or Python to implement statistical models, machine learning, and analysis (prediction, classification, clustering, time series forecasting, regression models, etc.). 
• Proficiency using one or more programming or scripting language like Python, R, SQL work with data. 
• Data visualization experience.   

Preferred Qualifications: 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, OR related field AND 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 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 data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• Solid partnership, collaboration, and interpersonal skills. 
• Experience with experiments, machine learning, deep learning, anomaly detection, predictive analysis, exploratory data analysis, and other areas of data science. 
• Engineering experience using large data systems on SQL, Hadoop, Hive queries, etc.  
• Experience driving data science practices & methodology improvements across disciplines including Finance, Marketing and Engineering. 
• Experience in B2C product growth from 0-1 phase and using data science to lead major growth efforts. 

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.

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