Data Scientist - AI Platform

Workday•Atlanta, GA

2d•$130,000 - $219,400•Hybrid

About The Position

As Workday accelerates its strategic evolution toward a consumption-based pricing model, the Platform Consumption Console (PCC) team is building the critical infrastructure to make it happen. We are the central nervous system for usage data across the enterprise. By engineering seamless data ingestion pipelines, pinpoint-accurate billing calculations, and transparent customer-facing controls, PCC empowers Workday to confidently launch flexible, usage-based products—like Workday Agents—that will drive the next generation of our global business growth. 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.

Requirements

5+ years of hands-on experience in Data Analysis and visualization.
5+ years of experience programming in Python, R, and SQL
Machine Learning and Data Science Knowledge/Skills
Substantial coding knowledge and experience in one or more languages: for example, Python/Jupyter, R, SAS, Scala, Excel, MATLAB, SPSS, C++, etc.
Strong experience with popular database programming languages including SQL, PL/SQL for relational databases is required

Nice To Haves

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.
Exposure to other programming languages, such as Java, Go is a plus.
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.

Responsibilities

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.
Machine learning (ML) modeling, management and problem analysis, data exploration and preparation, data collection and integration and operationalization.