Data Scientist - NLP/GenAI

Lifelancer
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist - New

Data Scientist - Imaging - Remote - Outside IR35

Data Scientist - Workforce Modelling

Data Scientist (Predictive Modelling) – NHS

Job DescriptionAre you a data scientist with experience in natural language processing, machine learning, and advanced analytics, and looking to apply your expertise in a collaborative and intellectually stimulating environment? Are you passionate about the future of healthcare?Our enterprise-wide data science, data engineering and product team is looking for a data scientist with experience in natural language processing and a passion for addressing business needs through data analysis and solutions. You will work on a highly collaborative, centralized team of data scientists, engineers, and strategists to deliver analytical insights and data products that drive value and impact for our highest priority business needs. Youll work side-by-side with internal partners across development, clinical, commercial, and general and administrative areas to develop creative NLP solutions that contribute meaningfully to our business and patients.

Key Duties and Responsibilities:
Collaborate with a centralized team of data scientists/engineers/strategists and cross-functional partners to conceptualize and deploy data science solutions for business problems using NLP (including but not limited to large language models), and to design and execute A/B tests to quantify the value of these solutionsBuild and deliver compelling data visualizations and outputs to communicate findings to technical collaborators, non-technical audiences, and business leadersParticipate in the broader data science community to stay current with methodology, software, and data development and availabilityBring an entrepreneurial and ethical mindset, openness, transparency, and collegiality to your work

Minimum Qualifications:

  • Bachelors, Masters, or PhD degree in a computational or quantitative discipline, including but not limited to data science, statistics, computer science, computational linguistics, biomedical informatics, neuroscience, physics, epidemiology, health economics
  • 2+ years of experience developing and/or applying ML/NLP solutions in an industry or academic context
  • Expertise in programming languages (e.g. Python, R, SQL, JavaScript), version control, and other data science related tools (e.g. Shiny, D3, AWS, dbt)
  • Expertise in working with natural language data and building text-based products, using both classic and state of the art NLP techniques (e.g. text mining, word embeddings, transformer-based models)
  • Experience with LLM prompt engineering and familiarity with LLM-based workflows/architectures such as retrieval-augmented generation
  • Experience with statistical/analytical methodologies and algorithms (e.g. classification, regression, clustering, feature selection/engineering, deep learning, time-series analysis, network analysis, hypothesis testing)
  • Exceptional communication skills and ability to present findings to non-technical audiences
  • Experience in effective data visualization approaches and a keen eye for detail in the visual communication of findings
  • Demonstrated history of adherence to highest standards of data ethics



Preferred Qualifications:

  • 3+ years of industry NLP data science experience
  • Familiarity with data product UX/UI design and testing
  • Familiarity with LLMOps, including deployment, monitoring, and maintenance of data solutions
  • Prior experience with using advanced analytics and/or developing advanced data visualizations and dashboards (e.g. R Shiny) in business settings
  • Prior exposure to clinical data, real-world data (EMR, claims), manufacturing or supply chain data, or life sciences-related research data
  • Knowledge of the biopharma or healthcare industry

Lifelancer (https://lifelancer.com) is a talent-hiring platform in Life Sciences, Pharma and IT. The platform connects talent with opportunities in pharma, biotech, health sciences, healthtech, data science and IT domains.

Please use the below Lifelancer link for job application and quicker response.

https://lifelancer.com/jobs/view/03a255e00a47a9fd4eb410dbbda91ec6

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.