About the Team

About the Role

As a Data Scientist, you'll lead cross-functional data science efforts to understand business requirements and design, build, and implement innovative solutions that enhance statistical modeling, measure value delivery and inform product decisions.

The bulk of the work will be in machine learning (ML) modeling, management and problem analysis, data exploration and preparation, data collection and integration and operationalization.

Ground-Floor Enterprise Impact: You are joining at a pivotal inflection point. PCC is rapidly transitioning from a localized billing tool into a core piece of Workday’s enterprise infrastructure. The work you do here will directly shape how Workday monetizes its products for years to come.

Massive Technical Scale: This is not a maintenance role. You will tackle complex, high-stakes engineering and product challenges—from orchestrating the ingestion of massive daily usage metrics and ensuring zero-defect financial ledgers, to building intuitive, high-visibility dashboards for our enterprise customers.

A "Startup Within a Giant" Culture: We are transitioning to a highly focused, domain-driven platform model. For builders who want to define strategy, establish new technical standards, and see the immediate impact of their work, this is the place to be.

About You

Basic Qualifications:

• 5+ years of hands-on experience in Data Analysis and visualization. 

• 5+ years of experience programming in Python, R, and SQL

Other Qualifications:

- Machine Learning and Data Science Knowledge/Skills
- Substantial experience in one or more of the following commercial/open-source ML framework/tools: Amazon SageMaker, Python/R, RapidMiner, Alteryx, H2O, TensorFlow.
- Substantial expertise in solving propensity to buy, segmentation, next-likely purchase/tactic, time series forecasting, churn and retention analysis, text analytics problems is preferable.
- Knowledge and experience in statistical and data mining techniques: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, etc.
- Substantial coding knowledge and experience in one or more languages: for example, Python/Jupyter, R, SAS, Scala, Excel, MATLAB, SPSS, C++, etc. Exposure to other programming languages, such as Java, Go is a plus.
- Strong experience with popular database programming languages including SQL, PL/SQL for relational databases is required, exposure to non-relational databases such as NoSQL/Hadoop-oriented databases such as MongoDB, Cassandra, others is a plus.
- Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Kafka is a plus.
- Knowledge of SaaS business preferred.
- Experience in the B2B software industry is preferred.
- Degree in computer science, data science, operations research, statistics, applied mathematics, or a related quantitative field is preferred or equivalent on-the-job experience. Alternate experience and education in equivalent areas such as economics, engineering or physics, is acceptable. Experience in more than one area is strongly preferred.

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below.  Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please .

Our Approach to Flexible Work
 

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.