Senior Lead Data Scientist

About GlaxoSmithKline:

At GSK, we are dedicated to improving the quality of human life by enabling people to do more, feel better, and live longer. As a global leader in pharmaceuticals and healthcare, we have a rich history dating back to the 19th century and a relentless commitment to advancing healthcare for the betterment of humanity.

Our Mission:

Our mission is to help people around the world do more, feel better, and live longer. We achieve this by researching, developing, and providing innovative medicines, vaccines, and consumer healthcare products. Our dedication to scientific excellence and ethical practices guides everything we do.

Job Overview:

The Senior Lead Data Scientist is a senior technical leader responsible for designing, developing advanced data and AI solutions, with a strategic focus on leveraging Generative AI technologies (e.g., large language models, diffusion models, multi-modal systems) to solve complex business problems. This role combines deep expertise in data science, machine learning, and AI architecture with a strong understanding of product strategy, cross-functional leadership, and ethical AI deployment.

Key Responsibilities:

• Design and implement advanced solutions utilizing Large Language Models (LLMs).

• Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions.

• Conduct research and stay informed about the latest developments in generative AI and LLMs.

• Develop and maintain code libraries, tools, and frameworks to support generative AI development.

• Participate in code reviews and contribute to maintaining high code quality standards.

• Possess strong analytical and problem-solving skills.

• Demonstrate excellent communication skills and the ability to work effectively in a team environment.

Skills & Qualifications:

Must Have Skills:

• 7 to 12 years of experience in IT

• Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation.

• Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis.

• Generative AI: Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities.

• Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as RLHF.

• Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP.

• Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git.

Tech Skills:
Machine Learning (ML) & Deep Learning

•  Solid understanding of supervised and unsupervised learning.

•  Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc.

Generative AI:

•  Hands-on experience with models such as OpenAI, Gemini etc.

•  Knowledge of optimizing large language models (LLMs) for specific tasks.

Natural Language Processing (NLP):

• Expertise in NLP techniques, including text preprocessing, tokenization, embeddings, and sentiment analysis.

• Familiarity with NLP tasks such as text classification, summarization, translation, and question-answering.

Retrieval-Augmented Generation (RAG):

• In-depth understanding of RAG pipelines, including knowledge retrieval techniques like dense/sparse retrieval.

• Experience integrating generative models with external knowledge bases or databases to augment responses.

Search and Retrieval Systems:

• Experience with building or integrating search and retrieval systems, leveraging knowledge of Elasticsearch, AI Search, ChromaDB etc.

Prompt Engineering:

• Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality and ensure desired results.

• Understanding how to guide large language models (LLMs) to achieve specific outcomes by using different prompt formats, strategies, and constraints.

• Knowledge of techniques like few-shot, zero-shot, and one-shot prompting, as well as using system and user prompts for enhanced model performance.

Programming & Libraries:

•  Proficiency in Python and libraries such as PyTorch, Hugging Face, etc.

•  Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure).

APIs & Integration:

• Ability to work with RESTful APIs and integrate generative models into applications.

Evaluation & Benchmarking:

• Strong understanding of metrics and evaluation techniques for generative models.

Good to Have Skills:

• Advanced Degree: Master’s degree in computer science or relevant field.

• Life Sciences Experience: Experience in Life sciences/Healthcare Industry

• Azure Certification: Azure Cloud experience/certification.

• Experience with Multi-modal AI models (text-to-image, text-to-video, speech synthesis, etc.).

• Knowledge of Knowledge Graphs and Symbolic AI .

• Understanding of MLOps and LLMOps for deploying scalable AI solutions.

Inclusion at GSK:

As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.

Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.

Skills

Generative AI, Large Language Models (LLMs), Machine Learning, Microsoft Azure, Natural Language Processing (NLP)

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

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