Data Scientist, Industry Solutions Engineering

The Industry Solutions Engineering (ISE) team is a global engineering organization that works directly with customers looking to leverage the latest technologies to address their toughest challenges. We work closely with our customers’ engineers to jointly develop code for cloud-based solutions that can accelerate their organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more with the cloud. We pride ourselves in making contributions to open source and making our platforms easier to use.

ISE is part of the Microsoft Industry Solutions organization and is a global organization of over 16,000 strategic sellers, industry experts, elite engineers, and world-class architects, consultants, and delivery experts who work together to bring Microsoft’s mission of empowerment – and cutting-edge technology - to life for the world’s most influential customers. We are on the front lines of innovation, working side-by-side with customers to drive value across the entirety of their digital transformation journey.

Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!

We are hiring Data Scientists with deep experience in data management and expertise in developing statistical techniques to analyze data and find patterns. As part of our team, you will be working side-by-side with high-impact engineers and strategic customers to solve complex problems. You will communicate trends and innovative solutions to stakeholders. You will work cross-functionally with several teams including crews, product teams, and program management to deploy business solutions.

Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!

Responsibilities

Business Understanding and Impact

• Leads data-driven projects with business acumen and data science expertise.

Data Preparation and Understanding

• Manages data collection and preparation for projects.

Modeling and Statistical Analysis

• Applies machine learning solutions and algorithms to achieve objectives, prepare and evaluate data, and communicate findings and risks.
• Writes scripts in various languages and understands Microsoft AI and Machine Learning tools.
• Designs experiments and operationalizes models at scale. Coaches other engineers on best practices.

Evaluation

• Understands relationship between selected models and business objectives.
• Ensures clear linkage between selected models and desired business objectives.
• Defines and designs feedback and evaluation methods.
• Coaches and mentors less experienced engineers as needed.
• Presents results and findings to customer stakeholders.

Industry and Research Knowledge/Opportunity Identification

• Provides feedback, coaching, and support to engineering team and other teams based on business knowledge, technical expertise, and industry trends.

Coding and Debugging

• Demonstrates excellent coding and debugging skills across multiple features/solutions.

Business Management

• Drives business value by collaborating with stakeholders and improving solutions.

Customer/Partner Orientation

• Provides customer-oriented insights and solutions by understanding the business, product, data and customer perspective.

Other

• Delivers customer-oriented solutions and builds trust with Microsoft products.
• Using your understanding of data science and a project’s problems, you’ll uncover important factors that can influence outcomes of specific products. You’ll also produce a project plan and be able to explain the relation between data science and the customer’s business strategy in non-technical terms.
• You will acquire the data necessary for your project plan and develop usable data sets for modeling. You’ll also update internal best practices for data collection and preparation, and contribute to data integrity conversations with customers.
• You will evaluate your team’s models and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale. You’ll also conduct thorough reviews of data analysis and modeling techniques, and identify and invent new evaluation methods.
• You will be performing extensive exploratory data analysis on large datasets to identify patterns, trends, and relationships. This involves applying statistical techniques such as hypothesis testing and regression analysis, as well as performing data cleaning, preprocessing, and addressing missing data, outliers, and anomalies to ensure high data quality and reliability.