CX Data Scientist

Key Skills

Big Data Technology, Python Programming, R Programming, SQL

Job Description

The Qualtrics XM Platform™ is a system of action that helps businesses to attract customers who stay longer and buy more, to engage and empower employees to do the best work of their lives, to develop breakthrough products people love, and to build a brand people can’t imagine living without.

Joining Qualtrics means becoming part of a team bold enough to chase breakthrough experiences - like building a technology that will be a force for good. A team committed to diversity, equity, and inclusion because of a conviction that every voice holds value, with a vision for representation that matches the world around us and inclusion that far exceeds it. You could belong to a team whose values center on transparency, being all in, having customer obsession, acting as one team, and operating with scrappiness. All so you can do the best work of your career.

We believe every interaction is an opportunity. Are we yours?

The Challenge:

As a data scientist in the Qualtrics Global Customer Intelligence team, you will develop models using customer feedback, product usage and operational data which will strategically advance how Qualtrics measures, understands, improves, and innovates the experiences it delivers to its customers.

What Success Looks Like:

In this role, you will support Qualtrics’ customer-facing teams with your expertise in data science. You will be part of a growing analytics team that serves our customer service teams with insights that can be turned into action. Whether you’re speaking with the Head of Customer Success, Global Operations or Product Delivery, you'll constantly be challenged to come up with new and creative solutions to help Qualtrics meet the needs of our customers.

Bring your analytical mind, problem-solving skills, and deep expertise in statistics and machine learning to turn data into insights that drive action our team can take to improve their customer experience and business outcomes. If you love solving problems with statistical theory, hands on coding, hacking, partnering with cross-functional teams and thrive in a fast-paced and dynamic environment, this position is for you!

A Day in the Life:

• Design, develop, and program methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions t
• Interact with cross-functional business stakeholders to understand their questions and issues and formulate approaches for data analysis and experiments
• Develop and code software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources
• Identify meaningful insights and findings from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments in ways business audiences understand
• Clearly communicate complex modeling outcomes and insights to business stakeholders
• Be an internal leader in statistics including descriptive statistics, correlation, and regression
• Form collaborative relationships with key stakeholders and team members

Qualifications & Requirements

• Master’s Degree in Business Analytics, Data Analytics, or Data Science, with a BA/BS in Economics, Finance, Management, Marketing, or Social Science
• 5+ years work experience
• At least 3+ years experience in open source programming languages
• At least 3+ years experience with machine learning
• Fluent in Python or R, able to query data using SQL, has experience working with cloud-based computing platforms and big data tools
• Strong verbal and written skills to present analysis and insights including trends and opportunities to stakeholders across the business
• Able to work independently on projects with little to no guidance required
• High standard of quality, attention to detail, and professionalism

Preferred Qualifications

• Familiarity with survey scripting and data reporting platforms such as Qualtrics is desired
• Ph.D. in quantitative discipline such as Statistics, Economics, Mathematics, Engineering, etc.