Senior Data & Applied Scientist

Last updated one month ago
Location:Redmond, Washington
Job Type:Full Time

Microsoft’s Cloud and AI group has a unique opportunity at the intersection of cloud computing and artificial intelligence. Fueled by Microsoft's cloud-first vision, we are disrupting the cloud industry with innovation and large-scale AI implementation.

The goal of the Azure Customer Growth & Analytics (CGA) team is to foster a data-driven culture; to encourage and enable the entire organization to make more informed decisions through data. In support of this mission, our machine learning team carries out applied research in ML/AI and designs, develops and deploys state of the art algorithms for various business scenarios. Some of the more recent developments include applications of deep learning, neural networks, boosted decision trees, sparse linear models, and customer segmentation, which have been executed in partnership with teams across engineering, finance, business planning, and sales and marketing. Our team also has a strong presence in both internal and external data science and AI/ML conferences.

We are looking for a passionate, talented, and innovative ML Scientist/engineer with a strong machine learning and deep learning background to help build industry-leading solutions. As a senior ML scientist in the Azure CGA team, you'll collaborate with partner teams and other researchers at Microsoft to build new ML solutions to solve critical and complex business problems. As part of this process, and with support from our data platform and engineering team, you will be working with huge volumes of data to solve real-world data science problems. In this team, your focus will be to apply/innovate state-of-the-art algorithms and techniques to solve complex problems on time series like forecasting, pattern detection and anomaly detection.

If you are seeking an iterative, fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve extreme-scale real world delivery challenges, and have business impact on global scale, this is your opportunity. Join us and be a part of an exciting team that is shaping the evolution of cloud computing



  • Develop new predictive and prescriptive models using advanced research techniques with a goal of productionalized solutions.
  • Collaborate closely with Analytics, Engineering, and Experimentation teams by demonstrating cross-functional resource interaction to deliver ML models.
  • Identify and investigate new technologies, prototype and test solutions for product features, and design and validate designs that deliver an exceptional user experience.
  • Combine broad and deep knowledge of relevant research domains with the ability to synthesize a wide range of requirements to make significant contributions to the feature roadmap for the applied machine learning platform.
  • Take responsibility for technical problem solving, including creatively meeting product objectives and developing best practices.



  • PhD in Computer science, Electrical Engineering, Physics or related field with strong focus on machine learning.
  • 4+ years of industry experience in handling high volumes of structured and unstructured data, with a proven track record of leveraging data science practices to drive significant business impact. Quantitative methods should span Deep Learning, statistical modeling, machine learning, optimization methods, econometrics, graph theories and NLP.
  • Expertise in time series forecasting, segmentation, pattern classification and anomaly detection with experience with Hierarchical Forecasting, Deep Learning, Bayesian Forecasting, Probabilistic Programming
  • Adapt ML and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP and GPU).
  • 2+ years of experience in applying deep learning models.
  • Expert in more than one more major programming languages (Java, C++ or similar) and at least one scripting language (Python, Perl, or similar)
  • Experience with open source tools like CNTK, Tensor flow, MxNet, Caffee and OpenCV and Big data technologies like Hive, PySpark, SparkR, Databricks etc.
  • Outstanding research track record in related areas, with evidence through academic publications and services


  • 6+ years of industry experience in handling high volumes of structured and unstructured data
  • PhD in computer science with focus on machine learning, deep learning, reinforcement learning, natural language processing
  • Scientific thinking and the ability to invent. Demonstrated track record of thought leadership and contributions that have advanced the field.
  • Top-tier publications (NIPS, PAMI, CVPR, ICML etc.)
  • Solid software development skills are plus.
  • Knowledge and experience working within cloud computing environments such as Azure or AWS.
  • Highly motivated to achieve results in a fast-paced environment.

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.