Data Scientist Microsoft
Redmond, WA

Job Description

AI for Humanitarian Action, AI for Earth, AI for Accessibility, and Digital Crimes. These are some of the programs at Microsoft where you can apply your world-class expertise to have a huge impact on global and local challenges. Come to work every day and contribute to projects that help save lives, alleviate suffering, and restore human dignity. Use the power of technology and AI to promote human rights, increase accessibility for those with disabilities, and seek solutions to climate change.

These are ambitious aims but with access to our technology, resources, global scale, and genuine commitment to using the power of AI and technology for good, they are achievable. We call this AI for Good and we empower our partners across the globe with our research, platforms, and technology.

Researchers and Data Scientists have a fantastic opportunity to join a newly created AI for Good Research Lab that is led by Microsoft's Chief Data and Analytics Officer. As a part of this team, you will get an opportunity to work at the cutting edge of data science with some of the brightest minds in the field, whilst knowing that you are generating solutions to some of the most demanding and defining challenges of our time.

These newly created roles will report to the Senior Director of Data Science and work closely with teams across Microsoft to deliver world class solutions to some of the world's most pressing problems.

Skills/Experience:

* Completed Master's Degree in a quantitative field. Ph.D. strongly preferred.
* Practical experience delivering insights and capabilities through data science using AI or machine learning techniques (neural networks for NLP, computer vision, etc.), supervised learning algorithms, such as Random Forest, and unsupervised learning algorithms such as clustering and PCA.
* Working experience with a numerical programming language such as Python/NumPy/SciPy, R, MATLAB, or similar
* Familiarity with SQL or similar.
* Strong experience or research using computational aspects of one or more of the following, or highly related, areas: Bayesian modeling, causal inference methods, finite mixture models, generalized linear models, joint modeling, and/or nonlinear mixed models.
* Comfort manipulating and analyzing complex, high-dimensionality from varying sources to solve difficult problems.
* Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
* Experience framing and participating in data-driven business decisions, including measuring and evaluating outcomes.
* Excellent oral and written communication skills.
* The ability to translate data science to non-technical people at all levels.
* Team player mindset with proven ability to build trusted relationships.
* Demonstrated ability to work efficiently, prioritize workflow, and meet demanding deadlines.

Skills/Experience nice to have

* Experience with CNTK, Tensorflow, Keras
* Experience with cloud based architectures such as Azure or AWS

Key responsibilities:

* Create machine learning solutions, including artificial intelligence, for a diverse set of problems.
* Employ structured approaches to leveraging large data sets to uncover new insights.
* Work closely with data analysts, data engineers, business and project stakeholders and incorporate their expertise into your solutions.
* Drive acquisition of new data sources as needed with governance on license, terms of use, compliance, quality, and high availability.
* Represent our capabilities and product offerings to internal and external leadership audiences, both technical and non-technical.
* Advance the research agenda for AI for Good initiatives: Prepare technical papers and presentations, and publish them internally and externally.
* Our research philosophy encourages knowledge sharing. In this position, you will be encouraged to contribute to the AI for Good research community by publishing papers, collaborating with leading academic institutions, and speaking and participating at leading industry events.