Data Scientist – NLP/GenAI

Job title:

Data Scientist – NLP/GenAI

Company

Lifelancer

Job description

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 workMinimum 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 ( ) 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.

Expected salary

Location

London

Job date

Sun, 04 Aug 2024 22:23:10 GMT

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