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 Team

About the Role

The team is seeking someone with a strong product mentality and opinions around how ML can drive a better customer experience. You will play a key role in building and deploying data-driven ML solutions that drive smarter products. You will effectively engage with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutions. You must have a mentality of continuous improvement, passion for quality, scale, and security.

About You

What you will do:

• Work with PMs to propose algorithm design, plan and implement algorithm fine-tuning and outline and implement validation strategy

• Independently identify ML opportunities and propose solutions to leadership

• Develop, train, and test ML models to use to address business problems

• Work with engineering teams to implement/refine models while considering functionality for recommendation output;

• Run regular A/B tests, capture data, perform statistical analysis, draw conclusions on the impact of your models 

• Undertake statistical analysis of the results produced and refine the model where requirer

• Experience with data wrangling, preprocessing, and feature engineering, especially with noisy data.

• Proven understanding of machine learning algorithms (supervised, unsupervised) and model evaluation techniques.
  Ability to define and track and identify key product metrics.
  Excellent communication and teamwork skills.

• Review and choose the best and most appropriate annotated datasets for the best-supervised learning methods

• Use effective text representations to transform natural language into useful features

Basic Qualifications:

• 5 + years of proven experience delivering applied machine learning products, including taking a product through design, implementation, and to production

• 5+ years of developing Machine Learning driven features with Python (including NumPy, SciPy, Pandas, TensorFlow, Pytorch)

Other Qualifications:

• Strong programming skills in Python with proficiency in relevant libraries (pandas, scikit-learn, TensorFlow/PyTorch)

• Familiarity with data technologies (Hadoop, Spark)

• Knowledge of deep learning and NLP techniques

• Experience building Extract Transform Load (ETL) pipelines.

• Experience in designing and crafting experiments, A/B testing and data analysis in the domain of quality metrics for machine learning services

• Experience in analyzing the ML algorithms that could be used to solve a given problems and ranking them by their success probability

• B.A./B.S. in Computer Science, Statistics, Mathematics, or similar

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.

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.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!