Senior Machine Learning Scientist
At Sense Street, we are developing natural language understanding systems for capital markets. Our premise is simple: markets are conversations, and we aim to help investment banks and asset managers have better, more efficient conversations. Through our partnerships with global banks, we have access to datasets that have not been made available in the past. This allows us to create language models uniquely suited to capital markets while advancing the state-of-the-art. We are a venture backed company founded by professionals with experience spanning machine learning, trading, and quantitative research.
As an experienced ML expert in the Data Science team, you will part of an innovative team of machine learning researchers, engineers, and domain experts. Here you will have the opportunity to prototype novel methods to analyse linguistic corpora that are not widely available, and to contribute to the development of cutting-edge models, while learning about specialised topics in the financial domain. You will gain experience of company and culture creation in the nascent stages of our start-up journey.
- Provide scientific depth in a data science team including ML and NLP scientists and linguists.
- Design new ML tasks from raw data through new ML methods to finalised products that will be used by our customers.
- Drive innovation on tasks that are in a specialised domain and do not conform to standard NLP tasks.
- Think creatively and innovatively to produce effective models.
- MSc or PhD in a relevant subject.
- Two or more years of industry experience in deep learning.
- Extensive background in using and developing deep learning methods.
- Substantial understanding of deep learning methods and breadth of knowledge of different models and their potential applications.
- Interest for text and language tasks.
Nice to have:
- Knowledge of foreign languages.
- Experience with UNIX and cloud computing.
- Have good communication and collaboration skills.
- Have good analytical and organisational skills.
- Cooperate well with other professionals of different backgrounds.
- See the inherent value in a respectful and diverse workplace.
- Highly skilled team, flat hierarchy, and opportunities for mentorship.
- Ability to heavily influence platform and culture from an early phase.
- Flexible working, central London location, company share option scheme.
- Budget/time for books, training and attending conferences/hackathons.