Senior Data & Applied Scientist

Last updated 7 minutes ago
Location:Greater London
Job Type:Full Time

We are the Azure Customer Experience (CXP) organization - a fast growing team of customer-obsessed & passionate individuals that drive positive customer outcomes and experiences. Our team is seeking a Senior Data Scientist to join our applied data science team for our Services Hub product.

The vision of our group is to empower every Azure customer and service provider with best in class troubleshooting experience to recover their unhealthy azure resources. This mission requires a highly scalable, reliable, and constantly evolving infrastructure. We are a core backend platform team that enables all the services in azure to provide automated solutions to our customers in need. Our team is focused on building large scale platforms to host various Azure solution micro-services, deliver services to power interactive troubleshooting experiences.

Azure CXP is also responsible for the development of Microsoft Services Hub (http://serviceshub.microsoft.com). Services Hub supports three primary digital delivery modalities: A platform for performing customer IT health assessments, a catalog of IP that includes digital learning assets and workshops to help educate customers, so they can make the most of their IT environments, and a support case management experience that ties it all together. We have over 20,000 active customers and are working to improve our platform and the services we deliver to provide an exceptional and unparallel customer experience.  

The “Monocle” data science team within Services Hub Platform Engineering– is truly a cross collaborative team, comprised of both data scientists and full stack engineers, who deliver customer facing AI solutions at rapid pace. These data science solutions span “next-best-action" and content recommendation engines, risk models, root cause analysis models, and natural language processing (NLP) algorithms, along with their corresponding microservices and UI artifacts.

This scientist will be working on a broad array of initiatives with a critical focus on recommender systems Natural Language Processing (NLP), embeddings, deep learning, and risk classification. Other initiatives include CX/UX statistical analysis, sentiment analysis, anomaly detection, real time recommenders, time series, and clustering. This data science team works with Python, PySpark, SQL, data lakes, Databricks, Spark, GPU compute, Azure Kubernetes Service for inferencing, and other open source and Azure cloud technologies.

In addition to the technical expertise, we expect someone who will be obsessed about working closely with customers to build solutions that delight them and make them more efficient. We’re committed to helping the IT Professional get better value out of their Microsoft investment. The ideal candidate will ask challenging questions about what needs to be done and push for simple features that will deliver value.

Responsibilities

  • Develop new predictive and prescriptive models using advanced research techniques with a priority on delivering production features.
  • Provide thought leadership in data science algorithm development.
  • Ability to go beyond libraries and packages and get deep into the algorithms to innovate and improve customer experiences.
  • Collaborate closely with Analytics, Engineering, and CX/UX Experimentation teams by demonstrating cross-functional resource interaction to deliver ML models.
  • Contribute to Microsoft’s global Applied Data Science practices by novel research, presentations, and publications.

Qualifications

  • 2+ years of experience in at least 3 languages such as Python, R, SQL, Java or Scala.
  • 2+ years of industry experience in handling high volumes of structured and unstructured data to drive business impact.
  • 2+ Quantitative methods that include deep learning, statistical modeling, machine learning, optimization methods, recommendation systems, graph theories and NLP.

Additional Qualifications

  • Adapt ML and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP and GPU).
  • 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
  • Strong theory/algorithmic background and good understanding on how to apply advanced knowledge to solve real problems

Preferred Qualifications

  • 6+ years of industry experience in handling high volumes of structured and unstructured data
  • PhD in quantitatively rigorous discipline focusing on machine learning, deep learning, high performance compute, reinforcement learning, or 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 etc.)
  • Full stack software development skills and familiarity are a plus.
  • Knowledge and experience working within cloud computing environments such as Azure or AWS.
  • Highly motivated to achieve results in a fast-paced environment.

#AZCXP

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.

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