Data Scientist
Job Description
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.
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About the Team
Our Data Science and Innovation team focus on leveraging AI/ML to enhance decision-making, automate complex processes, and unlock actionable insights across the company. By building strong partnerships grounded in collaboration and trust, we design and deliver solutions that improve efficiency, optimize workflows, and empower various Workday teams (Sales, CX, Finance, etc) to focus on high-impact work—fueling Workday’s continued growth.About the Role
Prioritize, scope and manage machine learning projects and the corresponding key performance indicators (KPIs) for success.
Execute 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.
Identify data-driven/ML business opportunities.
Understand new data sources and process pipelines for both structured and unstructured data. Display drive and curiosity to understand the business process to its core.
Have deep knowledge of fundamentals of machine learning, data mining and statistical predictive modeling, and extensive experience applying these methods to real world problems. Able to integrate domain knowledge into the ML solution. Have extensive experience in model testing, such as cross-validation and A/B testing.
Collaborate with Data Engineers and other Business Technology(BT) teams to evaluate and implement ML deployment options. Establish best practices around ML production infrastructure.
Promote collaboration with other data science teams within the enterprise, encourage reuse of artifacts. Train business teams on basic data science principles and techniques.
Closely work with the Pune team for CI/CD of our AI products.
Keep abreast of the latest developments in the AI/ML field by continuous learning and proactively champion promising new methods relevant to the problems at hand.
About You
Basic Qualifications:
5+ years experience with a specialization in ML engineering or data science
4+ years of experience with Databricks
Other Qualifications:
4+ years of relevant hands-on experience in successfully launching, planning, executing machine learning projects. Preferably in the domains of segmentation, cross-sell/upsell propensity modeling, next-likely purchase/tactic modeling, time series forecasting, churn and retention analysis, text analytics/NLP, statistical methods, experimental techniques, etc.
Demonstrated ability in launching significant data science projects, that they can manage large data science projects and collaborate cross-functionally with diverse teams
Experience in applying ML and data science to support business functions such as Sales, Marketing, Services, Support and Finance.
Machine Learning and Data Science Knowledge/Skills
Experience in one or more of the following commercial/open-source ML framework/tools: Amazon SageMaker, Python/R, RapidMiner, Alteryx, H2O, TensorFlow.
Experience 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: Pyspark, Python, R, Scala, C++, etc. Exposure to other programming languages, such as Java, React 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.
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 click here.
Primary Location: USA.GA.Atlanta
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.
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.
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