|Job Type:||Full Time|
Are you someone with a passion for data, analytics, insights, and technology? Do you want to work on one of the largest data science teams at Microsoft, lighting up actionable insights that drive key business decisions for the entire Office365 organization?
The Insights, Data Engineering & Analytics team (IDEAs), is a central data science team for M365 engineering and marketing. The IDEAs Small Business Data Science team is looking for an experienced motivated, self-starter with a passion for digging insights out of big data and driving business impact.
Our team plays a key role in providing data and analytics for M365 and owns the end to end decision sciences charter that includes:
- Opportunity analysis, hypothesis generation, and translation of business problems into data science projects throughout the end-to-end customer lifecycle
- Application of advanced analytical techniques (behavior segmentation, churn prediction, purchase propensity, recommendation engine, forecasting, experimentation etc.) to drive customer value and business impact across engineering, marketing, product development, and finance
- Continuously improving our Machine Learning operational capabilities through research, experimentation, and process improvements to the way to build and deploy models
- Work as a member of the larger data science community within Microsoft
To be successful in this role you must be driven, self-directed, entrepreneurial, and focused on identifying and delivering the right results. You also need to have strong skills in written and oral communication, a can-do attitude, and the willingness to tackle hard problems in innovative ways. You must also thrive in a team environment that values cross team collaboration and building on the success of others.
- Design, prototype, implement and test descriptive, predictive analytics, forecasting, and causal inference models
- Work with data engineers to architect and develop operational models that run at scale
- Partner with teams to identify and explore opportunities for the application of machine learning and predictive analysis
- Communicate with technical and non-technical audiences, and contribute modeling expertise as a team player
- Identify and champion ways to improve the quality, scale, and speed of our machine learning capabilities
- Master’s degree or higher in Statistics, Math, Econometrics, Computer Science, Operations Research, Social Sciences with a significant quantitative component or other related field or equivalent training
- 5+ years of industry work experience in SQL and R or Python to implement statistical models, machine learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment
- Exceptional written and verbal communication to educate and work with cross functional teams
- Be self-driven, and show ability to deliver on ambiguous projects with incomplete or dirty data
- Experience on large scale computing systems like Azure, Spark, Hadoop, MapReduce and/or similar systems
- Experience with programming skills, e.g. Java, C#
- Experience with machine learning development environments and toolkits like Databricks, H2o.ai, Prophet, CNTK, TensorFlow, Spark
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.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.