at EcoVadis
Full TimeWork smart, have fun and make an impact!
Our purpose is to guide all companies toward a sustainable world.
EcoVadis is the leading provider of business sustainability ratings. Our solutions are backed by an international team of experts and powerful technology.
We analyze data and build sustainability scorecards that give companies actionable insights into their environmental, social and ethical risks.
Why apply to EcoVadis? Be a part of the global sustainability change in business. Grow your career. Work with extraordinary people.
Feel valued for your contribution.Learn more about our team and culture on EcoVadis careers page. If you have questions about the company or open roles you can chat with an insider.
We are looking for a highly motivated Senior Machine Learning Scientist (NLP) to join our growing AI Center of Excellence team, responsible for using machine learning and natural language processing to drive innovation across the organization and accelerate positive impact on our planet and society. You will be part of the team of 20 scientists and engineers delivering solutions for our product portfolio and enhancing operational excellence.
Your global responsibilities will include (but will not be limited to):
Working with large, complex data sets to solve challenging business problems by applying advanced analytical methods as needed
Articulating and translating business questions into technical solutions
Leveraging Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Data Factory) and Databricks to deliver end-to-end solutions
Building, benchmarking, and maintaining machine learning models
Promoting best practices in machine learning
Staying in close contact with customers to evaluate their needs and recommend solutions that increase customer satisfaction and drive business value
Staying on top of technology trends in the area of, but not limited to, AI and ML and apply this knowledge to the key challenges ahead of EcoVadis
Education and experience
PhD or Master’s degree in quantitative discipline (e.g., Statistics/Applied Math, Artificial Intelligence, Computer Science, Data Science, Physics)
5+ years of overall experience in machine learning and data mining techniques
Demonstrable experience in using machine learning techniques and algorithms for classification/regression problems in industry
Proficiency in Python and ML frameworks and libraries (e.g., TensorFlow, PyTorch)
Excellent understanding of architectures used in NLP, such as transformers and RNN models, and NLP tasks (e.g., named entity recognition(NER), entity linking, question answering, semantic search)
Ability to independently design testable software components in well scoped scenarios, with simplicity, observability and maintenance as key considerations, and to apply best ML and software development practices
Experience of cross-functional collaboration in the development of ML products and services (e.g., Engineers, Product Managers) is a plus
Skills, abilities and work standards:
Continuous Learner – Ability to continually develop and improve one’s skill and knowledge to perform effectively and adapt to change in the workplace. Development occurs through a variety of learning opportunities, seeking feedback, and individual reflection.
Personally Effective - Making use of all of the personal resources at your disposal (talents, skills, energy, and time) to achieve goals.
Authentic - Being honest and authentic in communication, feedback and strategy.
Results-driven - Setting high goals for themselves and others. They accomplish their goals by effectively working through challenges and demonstrate commitment to the company's goals.
Creative Problem Solver - Focused on improving their practices and results. They are open to new ideas and they maximize available resources.
Collaborator & Partner - Works effectively with others to achieve shared goals through cooperation, sharing knowledge, joint problem-solving, and celebrating success.
Our growing team in Spain is full of talented professionals from various fields who all share a desire to make sustainability real. We offer competitive salaries and support personal growth from day one.
This includes extensive onboarding, teammates' support and a brand new e-learning platform bursting with courses and modules. So you can learn new skills and fine-tune old ones!
In return for your expertise and energy, we offer:
Working organization benefits:
Compensation benefits:
Wellness and Healthcare benefits:
More:
Our hiring team looks forward to reviewing your CV and cover letter with a guaranteed response to every application. A new job with purpose awaits you!
Don’t fit all the criteria but still think you’d be a good candidate? Please apply anyway to give our hiring team the opportunity to assess your skills and to learn more about what you could bring to EcoVadis. We’re interested in hiring capable people, regardless of professional and educational background.
Can the hiring process be adjusted to suit my needs? Yes. We want everyone going through the hiring process with EcoVadis to feel confident that you are able to demonstrate your full potential. We welcome applications from disabled people, people with long-term health conditions, and neurodiverse candidates. If you need any adjustments, including the provision of interview questions, please let the hiring team know.
Our team’s strength comes from everyone’s uniqueness and is founded upon mutual respect. EcoVadis commits to equity, inclusion and reducing bias in our hiring processes. EcoVadis does not accept any form of discrimination based on color, national or ethnic origin, ancestry, citizenship, religion, beliefs, age, sex, gender identity, sexual orientation, neurodiversity, disability, parental status, or any other protected characteristic that makes you unique. In your application, we encourage you to remove personal information such as: photographs, marital status, number of children, religion, gender, residential postal code, university graduation date, past medical or parental leave(s) taken, nationality (instead, please state if you are legally eligible to work in the job region/country), university name (instead, please state any degrees obtained and the study major).
