We are looking for a talented NLP Data Scientist to join our team working across a modern, web-focused technology stack. We work in a fast-paced environment, utilising cloud based technologies to deploy our products to customers.
As an NLP Data Scientist, you will be joining Adarga’s expanding AI engineering team. Our AI engineering team have strong technical capabilities within data science combined with the ability to productionise their work.
In this role, you will be building and training NLP models to extract information which we use within a range of client-facing analytical products. You will be required to interact with our users and engineers, gathering relevant information to train models and articulate the performance of them, to seek industry leading results. You will be using your linguistic background to prepare and curate NLP datasets, as well as designing and managing annotation tasks for NLP.
We all know that the amount of unstructured data - emails, documents, social media, web content, images and video - is exploding. We also know that generating actionable intelligence from this data is time consuming and inefficient.
We think people should spend time doing the stuff that people do well, and let the machines do the stuff that machines do better. We apply our expertise to tackle our customers’ challenges, freeing people to do what they do faster and better. We build our AI and ML technology into products that are easy to deploy, manage and use. We want all our tools to augment and empower knowledge-intensive processes and to help our customers efficiently and effectively analyse large volumes of data.
Our customers are engaged in some of the most important and challenging work in the UK and around the globe, analysing billions of data points each day. The volume and complexity of their data is growing rapidly and represents a significant opportunity for us to make a positive and significant impact for our customers.
We have a small and growing team with decades of experience applying ML and AI in the real world. Our team specialise in Natural Language Processing, Complex Network and Graph Theory, Time Series Analysis, CI/CD Cloud Solutions, Distributed System Architectures and Microservices. We have senior bankers and junior developers, PhDs and self-taught hackers. Whatever your background, we hope you would like to find a home in our inclusive and diverse team.
We pride ourselves on our close academic relationships with many of the UK’s leading software engineering and ML universities where we aim to apply cutting-edge research as soon as it is viable to real world, client-led problems. We hold quarterly hackathons, where we take a break from the sprint rhythm, take some of those blue-sky ideas, and encourage ourselves to make something happen!
Adarga is one of the few companies in the UK making Artificial Intelligence work on the ground, today, in real products. If you have a passion for making products that analyse vast amounts of data faster, more accurately and more effectively, then why not help us build a better data future?
Academic qualifications in NLP or Linguistics
Good scripting and programming skills (e.g. Python)
Nice to have but not mandatory:
Good working knowledge of NLTK, Gensim
Experience with SpaCy, NumPy
Background in Statistics
Knowledge of word embeddings and their applications (Word2Vec, GloVe, ELMo, BERT, etc.)
Experience in manual corpus annotation, Linguistics, or Lexicography.
Practical experience with Agile development and Peer Code Review
Knowledge or experience in domain adaptation and multitask learning
Confident in presenting technical work to both technical and non-technical audiences
In addition to a competitive salary we offer options to all permanent employees. We offer 25 days per year holiday, annually increasing by 1 day for each year’s service to a maximum of 30 days. We also offer a Holiday Buys scheme, allowing employees to obtain another 5 days holiday (subject to certain conditions) for each holiday year. Our contracted hours are 37½ hours per week, with core hours dependent upon the employment location.