Data Scientist (NLP) London, England
Job description
We are building the global standard benchmark for AI maturity in business. Our product launch in January 2023 was covered by the New York Times (https://www.nytimes.com/2023/01/26/business/tesla-profit-stock.html?smtyp=cur&smid=tw-dealbook) and many other outlets.
Why join us:
- We are index experts. Our Co-Founders Alexandra Mousavizadeh and Annabel Ayles have more than 30 years of experience building complex indices that drive positive change in the world.
- We are building a cutting edge research team that uses the latest techniques in machine learning to build faster and better data collection and analysis tools.
- We are backed by some of the world's leading tech investors, including the backers of Revolut and the tech commentator Scott Galloway, and have built a network of advisors that includes the Global AI Lead at AWS, Mastercard's President of Cyber & Intelligence, Ocado's former CTO, the former CCO of the Alan Turing Institute, the Chair of the UK Government AI Council and the former Head of the UK Government Office for AI.
If you are interested in advancing your career at a fast-growing, innovative and impact-driven company, you can read about Our Values (http://www.evidentinsights.com/our-values) and Our Commitment to Responsible AI (http://www.evidentinsights.com/responsible-ai) here. Our commitments to diversity and inclusion are set out at the end of this job description.
The role
We are looking for a Data Scientist to support the development of the data collection and analysis tools that drive the Evident AI Index, our other Indices and our research products. Our Data Science team interrogates our data sources, makes improvements to our existing processes with the latest techniques in machine learning and natural language processing, and puts this data in context of the overall research products we offer. Your responsibilities include:
- Analysing and improving the rich data from the Evident database.
- Developing internal packages, tools and processes to collect data via programmatic techniques such as web-scraping or external APIs.
- Developing machine learning-driven automated processes to classify incoming data, identify trends and patterns and extract meaningful text from documents.
- Developing dashboards and visualisation tools to track data sources that support the wider business.
- Working with our Data Engineering team to productionise your scripts and tools, and champion good data and software practices.
If you do not fulfill all requirements in the job description, we encourage you to submit your application nonetheless.
Core skills
- Experienced Python developer with knowledge of machine learning and data collection techniques.
- Experience with data collection, data cleaning and ensuring data robustness
- Excellent verbal communication skills and a proven ability to communicate complex topics.
Nice to have
- Experience using SQL and/or Tableau.
- Experience in developing and productionising machine learning solutions, in particular natural language processing (NLP) or natural language understanding (NLU).
Our commitments to diversity and inclusion
- Evident is committed to encouraging equality, diversity and inclusion among our workforce, and eliminating all forms of discrimination. Our aim is for our workforce to be truly representative of all sections of society and our customers, and for each employee to feel respected and able to give their best.
- During our recruitment process, you will not be discriminated against for any of the following reasons: race (including colour, nationality, ethnic and national origin), age, disability, gender reassignment, being married or in a civil partnership, being pregnant or on maternity leave, religion or belief, sex or sexual orientation. If you need us to make certain changes (known as reasonable adjustments) to make sure you are not disadvantaged during the recruitment process, you should contact us as soon as possible.
- We strive to create a working environment free of bullying, harassment, victimisation and discrimination, promote dignity and respect for all, and value and recognise individual differences and the contributions of all staff.
