The Substrate App Platform group is part of Microsoft 365 Core Platform organization. This is an interesting point in time as M365 evolves from an email platform to a platform that enables a deep pipeline of Microsoft apps and services that leverage the Substrate’s scale and high-value data to deliver intelligent experiences to end users. We need the best to take the initiative and work with engineers across E+D and Microsoft to build the next-gen platform in the Substrate.
To deliver on our mission to empower people and organizations to achieve more, we need to analyze our large data sets to find opportunities for product and process optimization, improve user experience for our products and using models to test the effectiveness of different courses of action. You need to have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. You must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
The position is full-time and based in our Nairobi office.
Responsibilities
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze signals data from the substrate to drive optimization and improvement of product user experience.
Develop custom data models and algorithms to apply to data sets.
Coordinate with different functional teams to implement models and monitor outcomes.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Qualifications
Required Qualifications:
MS/BS in CS/EE/Applied Mathematics/Statistics/DS/ML or related fields.
3+ years of professional experience working with machine learning libraries and real world data science problems.
3+ years of professional experience in at least one scripting language (Python, NodeJS, Ruby, Perl).
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Preferred Qualifications:
A successful candidate will show skills in the following areas:
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Passion for problem-solving.
Good communication skills
Working in agile teams with strong customer focus
Experience in Azure, Exchange, or other cloud and distributed systems is a plus.
Apply via :
careers.microsoft.com
