Data Scientist - AI Platform

Workday Workday · Enterprise · Atlanta, GA

Data Scientist on the Platform Consumption Console (PCC) team, responsible for building critical infrastructure for a consumption-based pricing model. The role involves leading data science efforts to understand business requirements, design, build, and implement ML solutions for statistical modeling, value measurement, and product decisions. Key responsibilities include ML modeling, data exploration, preparation, collection, integration, and operationalization, with a focus on enterprise-scale data and financial ledgers.

What you'd actually do

  1. 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.
  2. machine learning (ML) modeling, management and problem analysis, data exploration and preparation, data collection and integration and operationalization.
  3. orchestrating the ingestion of massive daily usage metrics and ensuring zero-defect financial ledgers
  4. building intuitive, high-visibility dashboards for our enterprise customers.

Skills

Required

  • Data Analysis
  • Data visualization
  • Python
  • R
  • SQL
  • Machine Learning
  • Data Science
  • statistical modeling
  • data exploration
  • data preparation
  • data collection
  • data integration
  • operationalization
  • generalized linear model (GLM)/regression
  • random forest
  • boosting
  • trees
  • text mining
  • hierarchical clustering
  • deep learning
  • PL/SQL

Nice to have

  • Amazon SageMaker
  • RapidMiner
  • Alteryx
  • H2O
  • TensorFlow
  • propensity to buy
  • segmentation
  • next-likely purchase/tactic
  • time series forecasting
  • churn and retention analysis
  • text analytics
  • Scala
  • Excel
  • MATLAB
  • SPSS
  • C++
  • Java
  • Go
  • NoSQL
  • Hadoop-oriented databases
  • MongoDB
  • Cassandra
  • MapReduce
  • Hadoop
  • Hive
  • Kafka
  • SaaS business
  • B2B software industry

What the JD emphasized

  • 5+ years of hands-on experience in Data Analysis and visualization
  • 5+ years of experience programming in Python, R, and SQL
  • 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 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++
  • Strong experience with popular database programming languages including SQL, PL/SQL for relational databases is required
  • Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Kafka is a plus.

Other signals

  • ML modeling
  • data exploration and preparation
  • data collection and integration
  • operationalization
  • statistical modeling
  • measure value delivery
  • inform product decisions