The ALICE team is hiring!Alice is a project to direct Artificial Intelligence towards economic decision making.   We are building tools that combine state-of-the-art machine learning with econometrics to bring automation to economic decision making.   The heart of this project is a striving to measure causation: if you want to understand or make policy decisions in a complex economy, you need to know why the system moves the way it does.
Microsoft Research has a long tradition of work at the intersection of Economics and Computer Science, and this team brings together researchers from across Social Science, Computer Science, and Machine Learning.   The Alice project allows us to dramatically scale the success that we’ve had in adapting existing ML technology for economic applications and in developing new deep learning architectures for causal inference.   All our research is tied to concrete policy-relevant applications, including work on demand estimation and price optimization, on measuring effectiveness of advertising and sales strategies, and on the design of incentives for desirable healthcare and education outcomes.   The goal is to use AI to improve and democratize economic research while taking from economic theory to push the frontier of AI.
We are looking for a Data Scientist with strong analytical and developer skills to join our team to develop industry leading machine learning solutions. Successful candidates will have several years of experience analyzing data and developing models across a breadth of technology platforms. They should be driven by the desire to solve problems for partners whether by leveraging sophisticated custom machine learning models or straightforward data analysis.
In this role, you will be responsible for:
•      End-to-end execution of the data science process, from understanding business requirements, data discovery and extraction, model development and evaluation, to production pipeline implementation.
•      Develop and deploy solutions with Microsoft Partners for solving business problems using machine learning and predictive modeling techniques.
Skills & Qualifications
•      The ability and effectiveness of working in a significant technical problem domain, in the terms of plan, design, execution, continuous release and service operation.
•      Software engineering fundamentals, including coding, problem solving and data analysis skills
•      Passionate and self-motivated.
•      Ability to effectively work in collaborative multiple project team environment and ship production features in a fast-paced startup environment.
•      Good communication skills, both verbal and written.
•      Customer/end result/metrics driven in design and development.
•      The ability to self-teach in new domains.
•      MS or PhD in Computer Science, Economics, Statistics, Operations Research or other technical field.
•      5+ years of real-world experience with machine learning algorithms for classification, regression, clustering, reinforcement learning or dimensionality reduction with expertise in time series analysis.
•      Skilled in R and/or Python, experience with Pandas a plus.
•      Experience with one or more of the DNN frameworks, including CNTK, MXNet, TensorFlow, Caffe.
•      Experience with Cosmos/Hadoop/Spark.
•      Experience with application development practices and version control systems.
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 to email@example.com.