Data Scientist - AI Platform

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.

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; Work on machine learning (ML) modeling, management and problem analysis, data exploration and preparation, data collection and integration and operationalization; Tackle complex, high-stakes engineering and product challenges from orchestrating ingestion of massive daily usage metrics and ensuring zero-defect financial ledgers, to building intuitive, high-visibility dashboards for enterprise customers

Requirements

5+ years of hands-on experience in Data Analysis and visualization; 5+ years of experience programming in Python, R, and SQL; Strong experience with popular database programming languages including SQL, PL/SQL for relational databases

Nice to have

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; Knowledge and experience in statistical and data mining techniques: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning; Substantial coding knowledge and experience in one or more languages: Python/Jupyter, R, SAS, Scala, Excel, MATLAB, SPSS, C++; Exposure to other programming languages such as Java, Go; Exposure to non-relational databases such as NoSQL/Hadoop-oriented databases such as MongoDB, Cassandra; Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Kafka; Knowledge of SaaS business; Experience in the B2B software industry; Degree in computer science, data science, operations research, statistics, applied mathematics, or a related quantitative field, or equivalent on-the-job experience; Alternate experience and education in equivalent areas such as economics, engineering, or physics; Experience in more than one area

Benefits

Workday Bonus Plan or role-specific commission/bonus; Annual refresh stock grants; Comprehensive benefits; Flexible work schedule