Data Scientist for AI Innovation
hace 3 días
About the Role:
We are seeking a highly skilled Data Scientist to join our AI Factory team at BBVA. As a Data Scientist, you will be responsible for harnessing the power of Large Language Models (LLMs) in the financial industry. Your primary focus will be on managing and executing significant analytical projects within the DATA area.
Key Responsibilities:
- Coordinate with team members to align with our strategic objectives.
- Solve complex problems by working closely with cross-functional teams.
- Identify business opportunities and apply your data science expertise to these challenges.
- Ensure that all deliverables comply with Advanced Analytics discipline governance standards and best practices.
- Mentor and guide less experienced team members, helping them to grow in their roles and contribute to the overall success of our team.
About the Job:
Tasks Definition and development of the analytical cycle of solution evaluation:
LLM Model Evaluation:
- Assess and select appropriate LLM models for each business need.
- Execute LLM test plans, including the definition, construction, and obtaining of analytical metrics (performance/cognitive, technical, and business) capable of evaluating LLMs in both discriminative and generative modes.
- Refine (fine-tune) LLM models on new domain data (discriminative and generative).
- Iterative construction of training/fine-tuning/validation datasets, evolving them based on the understanding metrics obtained and case analysis.
- Methodology approach for A/B testing and definition of requirements for experiments.
- Support for the construction and validation of KPIs.
Experimental Development of Analytical Solutions:
- Construction of knowledge bases for the models, e.g., domain documents, unstructured information from the vertical, etc.
- Iterative construction of partial or complete analytical solutions, possibly integrating inferences from different models.
- Integration of the product and evaluation of its performance according to methodology.
- Execution of sprint-by-sprint analytical experimentation cycles.
- Specialist support to the cross initiative:
Technological Prospection and Experimentation Support:
- Technological prospection of advances and state of the art of current NLP (LLMs, foundational models, proprietary/open-source models, etc.).
- Experimentation support for specialized lines (e.g., fraud, marketing, UX, talent, and culture, etc.).
- Dissemination, demonstration, and transmission of technical concepts suitable for different corporate profiles.
Requirements:
- Training Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
- Specific Knowledge Experience in the life cycle of ML models, including research, selection, adaptation, testing, training, and monitoring/retraining.
- Advanced technical knowledge of LLMs: Discriminative/generative models, fine-tuning/prompt engineering, model optimisation, embedding elicitation and comparison, fine parameterisation, LangChain, etc.
- Data lifecycle management, including identification, prior exploration (EDA), transformation and adaptation to the model/problem, definition of training datasets, validation, testing, dataset tracing, etc.
- Knowledge of the risks inherent in NLP models, especially in their generative component (hallucination of facts, omissions, inherent biases, unpredictability, etc.).
- Experience in ML projects on cloud environments, preferably AWS.
- (Desirable): Experience in other cloud environments: Azure, Google Cloud Platform/Vertex AI.
- (Desirable): Experience in other on-premise environments (Datio/Datio Evo).
- Skills: Algorithms, Learning Management Systems (LMS) Administration, Machine Learning Algorithms, Machine Learning Model Management, Natural Language Programming (NLP)
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