Expoint - all jobs in one place

מציאת משרת הייטק בחברות הטובות ביותר מעולם לא הייתה קלה יותר

Limitless High-tech career opportunities - Expoint

Microsoft Data Applied Scientist 
United States, Washington 
92709102

11.06.2024

Required Qualifications:

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field

    o OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience

    o OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

    o OR equivalent experience.

  • Experience
    • in customer-facing, project-delivery, professional services, and/or consulting,
    • AND with open source machine learning library such as Scikit-Learn, Pandas, Seaborn and or similar,
    • AND with statistics/machine learning models or LLM models such as linear/nonlinear regression, Bagged and Boosted Trees, Bayes methods, Transformer and or similar.
  • Experience in
    • Anomaly detection algorithm design and implementations experience or online experiments design and implementations,
    • AND technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Other Qualifications:

  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
    • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

  • Bachelor's Degree in Computer Science, Data Science, Applied Mathematical or Statistics, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Master's Degree in Computer Science, Data Science, Applied Mathematical or Statistics, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Doctorate in Computer Science, Data Science, Applied Mathematical or Statistics, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.
  • 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
  • Top Tier conference/Journal publications related to anomaly detection, auto-diagnosis and experiments design and implementations.
  • Deep compute science knowledge (concepts such as CPU/Memory/TOR/ LB/Vnet/ VLan etc), and serverless architectures and other cloud architectural patterns.
  • Familiar with data visualization tools such as PowerBI, Networkx or similar.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities
  • Share accountability of a wide array of assets and be comfortable with learning a broad array of technologies.
  • Independently design and implement anomaly detection, auto-triaging/correlation, and causal inference model to deliver preventive insights to improve Azure cloud system availability, reliability, and efficiency
  • Work with partner teams to integrate the Insights into Azure daily dev operations and Azure system for automatic mitigation and repairs
  • Contribute towards driving visibility into customer impacting on Virtual Machines or Containers or higher-level Azure services built on top of Virtual Machines.
  • Assist with building an automated data quality solution to detect problems in downstream dependencies and take automated action to correct them.
  • Look for opportunities to share learnings and tools broadly within Microsoft and beyond. Specifically, our team does cutting edge work with Azure Data Explorer (Kusto) and makes a point at contributing back to the larger environment.