Data Scientist
Posted 1 week ago by Avance Consulting
Negotiable
Undetermined
Undetermined
Knutsford, England, United Kingdom
Summary: The role of Data Scientist involves supporting the design, development, and implementation of Generative AI models in alignment with Barclays' approved methodologies. The position focuses on applying machine learning solutions, particularly in Generative AI, while collaborating with various teams to drive data-informed product strategies and insights. Key responsibilities include experimenting with deep learning models, conducting customer data analysis, and leveraging data for actionable insights. The role requires hands-on experience in data science applications and machine learning pipelines, particularly with Generative AI projects.
Key Responsibilities:
- Experiment with, apply, and implement DL/ML models, focusing on Large Language Models (LLMs) and Generative AI techniques.
- Utilize various GenAI techniques to derive actionable insights, generate content, or create novel user experiences.
- Collaborate with product, engineering, and other teams to build Agentic systems for large-scale campaigns.
- Conduct in-depth analysis of customer data, market trends, and user insights to inform GenAI-powered solutions.
- Partner with product teams to design, administer, and analyze A/B and multivariate tests for GenAI-driven features.
- Leverage data to develop analytical insights and present findings on GenAI model performance to stakeholders.
Key Skills:
- 3+ years of hands-on experience in building data science applications and machine learning pipelines, with experience in Generative AI projects.
- Experience with Python for research and software development, including common GenAI libraries and frameworks.
- Experience with prompt engineering and utilizing pre-trained LLMs via APIs or open-source models.
- Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP).
- Proficiency with relational databases (e.g., SQL).
- Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI.
Salary (Rate): undetermined
City: Knutsford
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Role: Support the design, development and implementation of GenAI models aligning to the Barclays approved patterns and ways of working. You will play an important role in applying and implementing effective machine learning solutions, with a significant focus on Generative AI. You will work with product and engineering teams to contribute to data-driven product strategies, explore and implement GenAI applications, and deliver impactful insights.
Responsibility
- Experiment with, apply, and implement DL/ML models, with a strong emphasis on Large Language Models (LLMs), Agentic Frameworks, and other Generative AI techniques to predict user behavior, enhance product features, and improve automation
- Utilize and adapt various GenAI techniques (e.g., prompt engineering, RAG, fine-tuning existing models) to derive actionable insights, generate content, or create novel user experiences
- Collaborate with product, engineering, and other teams (e.g., Sales, Marketing, Customer Success) to build Agentic system to run campaigns at-scale
- Conduct in-depth analysis of customer data, market trends, and user insights to inform the development and improvement of GenAI-powered solutions
- Partner with product teams to design, administer, and analyze the results of A/B and multivariate tests, particularly for GenAI-driven features
- Leverage data to develop actionable analytical insights & present findings, including the performance and potential of GenAI models, to stakeholders and team members
Skillset
- 3+ years of hands-on experience in building data science applications and machine learning pipelines, with demonstrable experience in Generative AI projects
- Experience with Python for research and software development purposes, including common GenAI libraries and frameworks
- Experience with or exposure to prompt engineering, and utilizing pre-trained LLMs (e.g., via APIs or open-source models)
- Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP)
- Proficiency with relational databases (e.g., SQL)
- Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI