Data and Applied Science Manager

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Do you have a passion for applying Data Science models to solve complex problems? Do you want to help Microsoft engineer an industry-leading Intelligent Supply Chain, enabling end-to-end visibility, insights, and optimization? We are looking for a?Senior Data and Applied Scientist?Manager with strong leadership, analytical, and communication skills to join our expanding team. The ideal candidate has extensive expertise in machine learning and is passionate about creating business value through building robust teams delivering cloud-based solutions infused with AI. They should be comfortable with the end-to-end?ML/AI solutions development process, starting from understanding the customer business problem and ending with production implementation of machine learning pipelines.

At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. The Devices Supply Chain organization is critical to delivering on this mission, with responsibility for the end-to-end supply chain for Microsoft’s vast array of hardware products including the entire line of Surface devices and accessories, Xbox consoles and accessories, PC Hardware, next-generation products like Holo-lens, and more.

As part of the Devices Supply Chain organization, the Data Science team is leveraging Predictive & Prescriptive modeling to increase visibility & transparency, predict customer demand, streamline, and automate business processes, optimize inventory and capacity decisions, and much more. We develop and deploy Machine Learning and AI models, statistical methods, mathematical optimization, simulation, and other advanced analytical techniques to enable a variety of supply chain capabilities. For example, we forecast demand for all Microsoft devices globally, enabling our supply chain to match supply with demand and deliver a great customer experience while minimizing inventory investment.

As part of the role, you will work with a global diverse team of data scientists and engineers that apply machine learning and optimization to build industry solutions. To be successful, you will need software engineering skills, technical aptitude, communication skills, and a collaborative work style.

Responsibilities

• Grow and lead a team of Data Scientists and Data Engineers and ensure both your team and the organization embrace a culture of continuous learning. 
• Work with your business stakeholders to evaluate and select the right customer scenarios to ensure your team has high impact, interesting, and challenging projects. 
• Ensure your team adheres to solid engineering and rigorous data science principles, producing maintainable code and models and developing the team to be stronger engineers and scientists. 
• Analyze and resolve complex business and technical issues with internal stakeholders and customers. 

Qualifications

REQUIRED QUALIFICATIONS

• 8+ years of experience developing and deploying end-to-end ML/AI systems. We prioritize those with a broad set of skills: working with structured and unstructured data, data processing at scale, feature engineering, and model operationalization.
• Bachelor’s in computer science, Machine Learning, Data Science, or equivalent technical fields.
• Experience in leading a team and helping grow careers.

 PREFERRED QUALIFICATIONS

• Experience working within and directing geographically dispersed, diverse, and virtual teams.
• Experience managing both technical and non-technical stakeholders and able to resolve complex business and technical issues.
• We are looking for people who have broad Machine Learning experience across a variety of traditional and Deep Learning applications.
• Python skills, including the scientific Python stack, Machine Learning frameworks, and at least one major programming language such as C#.
• Demonstratable experience with software engineering principles, parallel and distributed computing, statistics, machine learning, cloud technologies like Azure, AWS, Google Cloud.