1 day ago
Copenhagen, Denmark or Stockholm, SwedenSenior
Responsibilities
- Research, develop, and implement advanced machine learning models and techniques.
- Design and implement robust data pipelines for machine learning.
- Lead exploratory data analysis, feature engineering, model building, and model development lifecycle activities.
- Deploy and scale machine learning models in production environments.
- Apply model monitoring and retraining strategies.
- Mentor and guide other team members.
Requirements
- 8+ years of experience in machine learning development.
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related discipline, or equivalent practical experience.
- Experience with deep learning, natural language processing, or computer vision.
- Strong data processing, data science, exploratory data analysis, feature engineering, and machine learning expertise.
- Strong proficiency in Python and data science and machine learning libraries.
- Understanding of software development principles and production model deployment and scaling.
- Working knowledge of Model-Based Design concepts.
- Strong collaboration skills and ability to mentor team members.
- A PhD in a relevant discipline is welcome.
Benefits
- Flexible work model requiring at least 50% of each quarter in the office or field, with remote home-office options.
- May be eligible for the Workday Bonus Plan or role-specific commission/bonus and annual refresh stock grants.
- Reasonable accommodations are available during the application process.
Tech Stack
Categories
About Workday
Workday builds cloud-based enterprise applications for human capital management and financial management, including payroll, time tracking, expenses, planning, and procurement, sold on a subscription basis with professional services. Founded in 2005 and headquartered in Pleasanton, California, it is a public company traded on NASDAQ as WDAY. Organizations worldwide use Workday to unify HR and finance data, automate processes, and apply AI to workforce and financial operations.