Data Engineer jobs in United States
Principal Consultant (AI Specialist), FT Strategies
Applied Intuition Inc.
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Methodfi
Product Engineering Data Scientist Soho, London
AnaVation LLC
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SEFE Marketing & Trading Ltd
Growth Data Scientist: Data Analytics & Dashboards
Crypto.com
Data Scientist Senior Consultant - Belfast
KPMG International Limited
Data Scientist - Deep Learning Practitioner
Capital One (Europe) plc
Data Scientist - Deep Learning Practitioner
Capital One
Sr. Data Scientist, GenAI Algorithms (Based in Dubai)
Talabat General Trading and Contracting Company
Data Engineering Manager
Trainline International Limited
Data Scientist
Job summary
A research organization in London is seeking a Data Scientist who will work on developing NLP applications and machine learning pipelines. The role includes building data collection systems, extracting insights, and requires fluency in English and Russian. Ideal candidates are expected to have a solid background in ML and NLP with experience in Python, AWS, and database technologies. This is a full-time position with dynamic team interactions.
Qualifications
- Proven experience in applying Machine Learning and NLP to real-world problems.
- Open-source contributions or technical publications preferred.
Responsibilities
- Develop and optimize NLP pipelines for data extraction.
- Build applications for data collection.
- Provide actionable insights from processed data.
- Manage projects independently from start to finish.
- Monitor and refactor deployed applications.
Skills
Tools
Location: London / Applicants must have the right to work in the UK — Visa sponsorship is not available for this role
Employment type: Full-time
As a Data Scientist at the NEST Centre, you will be part of our Data Science Team, working at the intersection of Natural Language Processing, Machine Learning, investigative journalism, and political science.
- Developing NLP pipelines and applications to extract structured data from texts (news articles, social media posts, etc.), disambiguate the extracted entities, and classify texts into categories of interest (e.g., topics, tags, sentiment classes).
- Building applications that automatically collect data on various entities from publicly available sources.
- Extracting actionable insights from collected and processed data to support the work of NEST Centre experts.
- Taking full ownership of the project: from conceptualisation and requirement gathering to writing production-grade code and deployment.
- Monitoring, refactoring, and ongoing optimisation of deployed applications.
- Comfortable working in a privately funded, startup-like environment, embracing its numerous uncertainties and responsibilities.
- A proactive, can-do attitude with the ability to work independently and manage tasks with minimal supervision.
- Fluency in English and strong reading comprehension in Russian, due to the Centre’s focus and the nature of the data processed.
- Solid theoretical background and practical experience in Machine Learning and Natural Language Processing, with a track record of applying these skills to real-world problems and delivering measurable value.
- Proficiency in the following technologies:
- Machine Learning frameworks in Python
- NLP frameworks such as Hugging Face (transformers, sentence-transformers, setfit) and/or others (e.g., Haystack, Flair)
- SQL (PostgreSQL or equivalent dialects)
- Vector databases
- AWS services, especially Lambda, S3, DynamoDB, ECR, EC2, ECS, SQS, and SNS
- Docker
- Git and GitHub.
- Adherence to programming best practices and clean code standards.
- Ability to demonstrate expertise through open-source contributions, technical blog posts, online courses, or co-authored academic publications.
- Opportunities for professional growth and development.
- Dynamic multi-cultural team.
- Creating impact through projects that advance global cooperation and security.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.