Your work days are brighter here.At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.About the TeamWorkday has built an Enterprise Data & Analytics Team to transform and optimize the way Workday builds and shares trusted data to drive insights and data led innovation across the enterprise. One of the key organizational principles of the group is the treatment of data and analytical assets as products with an agile methodology to support their continued development. Each data product will have a dedicated cross-functional Fusion Team to drive data onboarding, security, discovery, transformation, and analytics to create value in line with the business priorities. Join our team as we aim to deliver exciting new user-centered, predictive, and prescriptive reporting analytics at Workday!About the RoleThe Data Scientist designs, develops and programs methods, processes and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for businesses across Workday. They interact with product and service teams to identify questions and issues for data analysis and experiments. In this role, they will also: Release models into production and iterate on them using feedback data, ie using AB testing Guide and inspire the organization about the business potential and strategy of machine learningExecute machine learning lifecycle from ideation and hypothesis generation, data extraction and exploration, model building and validation, results communication, and productization to optimize go-to-market strategy.Understand new data sources and process pipelines, and catalog/document them. Display drive and curiosity to understand the business process to its core. Network with domain experts to better understand the business mechanics that generated the data.Responsibilities Build datasets using software engineering best practices, data management fundamentals, data storage principles, recent advances in distributed systems, and operational and engineering excellence best practices.Create shared data assets generating visibility into critical business metricsBuild and maintain automated data pipelines that transform data into clean and highly optimized assets to address continuously evolving analytical requirements.Create extensible and scalable data schema and pipelines that lay the foundation for downstream analysis using SQL and PythonPartner with business systems analysts, data quality engineers, and product managers to develop Workday data products.Analyze systems, review data models, develop transformations, and document the specifications.Identify and analyze multi-structured data from a variety of sources to assess its effectiveness and accuracy to meet analytics requirements.Demonstrate passion for quality and productivity by using efficient development techniques, standards and guidelines.Effectively communicate through technical documentation, commented code, and interactions with stakeholders and adjacent teams.About YouBasic Qualifications7+ years of experience in Natural Language Processing using deep learning (RNN, CNN, LSTM, etc.) 7+ years of experience working with Deep Learning Frameworks: Tensorflow, Keras, Pytorch, etc.7+ years of experience working with techniques such as model cross-validation and A/B testing.Other QualificationsAny experience with UX Analytics and/or UX datasets would give you a headstartExperience with graphs and graph databases for data modeling would be useful but not essentialExperience in one or more container ecosystems (Docker, Kubernetes, Mesos) is a plusA passion for innovation and ability to contribute to shaping the technical and product roadmapsProven ability to work in an agile, fast paced continuous delivery environmentFlexibility to understand and touch related areas of the codebase if necessary to unblock the data science work.Expert in training and inference pipeline creation and implementationStrong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical usersBachelor's degree or higher in computer science, data science, statistics, applied mathematics, or cognitive science is strongly preferredWorkday Pay Transparency StatementThe 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 click here.Primary Location: USA.CA.Pleasanton Primary Location Base Pay Range: $149,800 USD - $224,800 USD Additional US Location(s) Base Pay Range: $131,100 USD - $224,800 USDOur 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.Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
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