Data Scientist - Performance Engineering Workday
Pleasanton, CA

Job Description

Join our team and experience Workday!

It's fun to work in a company where people truly believe in what they're doing. At Workday, we're committed to bringing passion and customer focus to the business of enterprise applications. We work hard, and we're serious about what we do. But we like to have a good time, too. In fact, we run our company with that principle in mind every day: One of our core values is fun.

Job Description

Our ultimate goal is application performance that yields an excellent end user experience and scales to meet Software as a Service Infrastructure needs. We're looking for data scientist to join our team and work on a variety of initiatives from core product to new strategic projects. Where are the highest friction points on our platform and biggest opportunities to improve the application performance by using underlying tools and infrastructure efficiently? What would a financial end user experience look like and how should we measure the health of the financial services provided by WDAY.

An ideal candidate should possess a good balance of technical skills, business acumen, and communication skills. A driven individual who's keen to solve hard business problems is desired.

Experience/Skills/Education:

* 5+ years of experience in Software Engineering
* In depth knowledge of distributed systems in a public or private cloud
* Has led project or feature with complete ownership.
* Proven ability to succeed in both collaborative and independent work environments.
* Adapt, learn and deliver in fast-paced agile development
* Strong skills in SQL and distributed system optimization (e.g. Hadoop, Hive, Spark, Presto)
* Strong programming skill (Python, R, or Scala preferred).
* Experience in schema design and dimensional data modeling
* Ability to perform statistical analysis to inform business decisions
* Familiarity with experimentation and machine learning techniques
* Experience with an ETL framework like Airflow

Responsibilities

* Translate complex findings and results into a compelling narrative.
* Define and evaluate key performance metrics across infrastructure, tools, applications and understand what moves them and why.
* Partner with engineering to design robust logging and build quality data pipelines
* Investigate challenging questions around user experience to understand the voice of our user
* Ownership of conceptualizing, developing, and maintaining dashboards and visualizations
* Communicate analyses and recommendations to cross functional stakeholders for decision making
* Strategize on making analyses easily repeatable and accessible.
* Build tools to automate data science work (e.g. modify a function in Python or R)

Knowledge or Experience with the following a plus:

* Deep understanding of modern machine learning techniques and their mathematical underpinning, such as classification, recommendation systems and natural language processing.
* Proven ability to tailor machine learning solutions to business problems in a cross functional team.
* Industry experience in developing deep learning model is a plus

#LI-TL