Role and responsibilities
- Researching, analyzing, and building proofs of concept in the domain of machine learning and large-scale text data processing with application in finance (generating data for asset managers for systematic investing)
- Building solutions keeping in mind how they are controlled for quality in production
- Competent data scientist having experience with and deep understanding of machine learning models and deriving insights from real world data
- Working with a cloud-based environment is a plus
Behavior and knowledge:
- Previously demonstrated quickly gaining an understanding of a new domain or has Entis data domain experience (structured and unstructured related to companies and securities)
- Interested in new developments in the ML/NLP space
- Curious, investigative, and explorative mindset
- Team player, communicator, supportive, positive mindset, result driven
- Machine learning
- Strong data analysis skills
Nice to have:
- Large language models
- Azure Cloud (storage, Kubernetes and containers, SQL databases, Functions, virtual machines, etc.)
- Financial domain knowledge
What we are looking for
Entis is looking for students who want to support us to improve the quality of our sustainability assessments. This includes a wide variety of tasks, ranging from extracting relevant data to evaluating company documents according to established rules about what is sustainable and what is not.
• Affinity with sustainable solutions in the field of sustainable energy, health care, food, materials
• Works accurately and decisively
• Available 2-5 days a week
What we offer
We are flexible when it comes to working hours.
More than competitive salary.
Given the Covid-19 situation we expect you to work from home, except during the first week(s) when you’ll receive training on the methodology and tools used.
We adhere to the RIVM requirements for Covid-19.
If you’re interested, please fill in the form below
Entis is looking for students who want to support us to improve the quality of the Alpha signals. This includes a wide variety of tasks, for example:
- Checking if company’s historic corporate events reflected in our data correspond to the one that could be found online (Wikipedia, news websites)
- Checking if our ML and NLP models/functionality produced correct result and help with model training
- Helping with daily data management operations, particularly to inspect changes in data about companies to guarantee its quality
- Eye for detail, working accurately and decisively
- Interest in learning about financial markets, as well as about individual publicly listed companies
- Interest in working with ML and NLP functionalities
- Availability: 2-5 days a week
What we offer
- We are flexible when it comes to working hours
- More than competitive salary
- You are allowed to work from home
- We adhere to the RIVM requirements for Covid-19