IT and Telecoms

Data and Applied Scientist II – Digital Transformation Platform at Microsoft Nigeria

Microsoft Corporation is an American multinational technology company with headquarters in Redmond, Washington. It develops, manufactures, licenses, supports, and sells computer software, consumer electronics, personal computers, and related services. Its best known software products are the Microsoft Windows line of operating systems, the Microsoft Office suite, and the Internet Explorer and Edge web browsers.

At Microsoft our mission and values are to help people and businesses throughout the world realize their full potential.

We are recruiting to fill the position below:

Job Title: Data and Applied Scientist II – Digital Transformation Platform

Job number: 1208930
Location: Lagos, Nigeria
Travel: 0-25 %
Profession: Engineering
Role type: Individual Contributor
Employment type Full-Time

Job Description

  • As a foundational pillar of the company, the Digital Transformation Platform group is building the next generation of business applications and platforms that will help businesses large and small succeed in achieving their digital transformation agenda.
  • The products we are responsible for include Data platform, IoT platform, ML platform, Industry cloud, Dynamics 365, Power Platform (Power BI, PowerApps, Power Automate), Mixed Reality for business and other SaaS applications and workloads.
  • We are seeking a dynamic individual contributor for our Data Science function as part of our Insights and Analytics team. In this role, you will be responsible for delivering deep analytical insights to drive business success as well as productizing models to help drive usage growth of our products.


  • Applying statistical and machine learning techniques to problems like customer or user segmentation, classification, and clustering to understand usage trends and drivers of satisfactions
  • You will design experiments, analyze results, and produce actionable, trustworthy conclusions from them.
  • Present findings and recommendations to key decision makers at various management levels
  • Drive innovation leveraging Data Science and Machine Learning, to experiment with and establish new ways of driving customer engagement by leveraging data – ultimately resulting in usage and satisfaction growth
  • Engage with customers via public presentations and 1:1 meeting at all levels

Required Qualifications:

  • Bachelor’s, Master’s or PHD in Data Science, Mathematics, Operational Research, or related field.
  • 2+ years of hands-on experience with data science, big data experience and analytics in a business context.

Preferred Qualifications:

  • Experience with product and service big data telemetry systems.
  • Significant experience in Data Science and Machine Learning with a strong proven track record in delivering positive business impact .
  • Strong knowledge in applied statistics and mathematics
  • Significant experience of analytical programming languages such as R and/or Python.
  • Enjoy discovering and solving problems; proactively seeking clarification of requirements and direction; being a self-starter who takes responsibility when required.
  • Strong interpersonal, verbal, visual and presentation skills, ability to communicate complex findings in a simple manner to executives.
  • Ability to work collaboratively across multiple business and engineering teams
  • A willingness to learn, share, and improve.

How to Apply
Interested and qualified candidates should:
Click here to apply online


  • 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.

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