Senior Data Scientist

Overview

Do you enjoy solving problems, looking at problems through a different lens, and working closely with customers to innovate new solutions to complex problems? Do you jump with excitement at the opportunity to identify trends and provide unique business solutions? Do you want to join a team where learning about a new technology or solution is part of our work every day?

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 using, and making contributions to, open source and assisting our product teams to make our tools and platforms easier to use.

We develop solutions side-by-side with our customers through collaborative innovation to solve their challenges. This work involves the development of broadly applicable, high-impact solution patterns and open-source software assets that contribute to the Microsoft platform. In this role, you will be working with engineers from your team and our customers’ teams to apply your skills, perspectives, and creativity to grow as engineers and help solve our customers’ toughest challenges.

We are hiring a Senior Data Scientist with deep expertise in machine learning and AI and experience in developing production quality solutions which deliver a huge business impact. 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 engineering crews, product teams, and program management to deploy business solutions for Microsoft clients in the financial sector.

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!

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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 ML tools. Designs experiments and operationalizes models at scale. Coaches 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 senior 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 coding and debugging skills across multiple features/solutions.

Business Management

Drives business value by collaborating with stakeholders and improving solutions.

Customer/Partner Orientation

Delivers customer-oriented solutions and builds trust with Microsoft products

Qualifications

Required/Minimum Qualifications

• Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.

Additional or Preferred Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results))
• OR equivalent experience.
• 3+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
• Experience with Generative AI (GenAI) technologies, and Cloud services such as Azure.
• Demonstrated industry knowledge and experience in the financial sector.
• Experience in developing production-ready data-science solutions to address business challenges.
• Experience working as part of geographically dispersed, diverse, and virtual teams.
• Comfortable with travel up to 25%.
• Demonstrated ability to work with customers.
• Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year. There is a different range applicable to specific work locations, within the San Francisco - Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $153,600 - $250,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until July 30, 2024.