Data Scientist Analyst at BBVA transforming complex data into strategic solutions using machine learning. Collaborating within Banking Ops team to improve operational efficiency and customer experience.
About the role
- Entry-level data analyst supporting AI team in developing and evaluating AI products. Responsibilities include data exploration, performance monitoring, and cross-functional collaboration.
Responsibilities
- Data Exploration & Visualization: Investigating data to identify trends, anomalies, or patterns using tools like SQL, Tableau, Power BI, or Python libraries like Matplotlib or Pandas.
- Performance Monitoring: Analyzing the performance metrics of AI models such as accuracy, precision, recall, F1 score, etc., and identifying areas for improvement.
- Performance Hardening: Provide quantitative and qualitative insights for feature improvement, contributions in model development process through data or design.
- A/B Testing & Experimentation: Conducting experiments to test the efficacy of AI models or changes to AI systems, using A/B testing or other experimental designs.
- Root-Cause Problem Solving: Carry out failure investigation of AI events including but not limited to recalling and reviewing events where AI algorithms fail in the field and then compare to backtest (test infra) results in consultation with model development team and jointly layout directions for feature improvements.
- Reporting: Creating dashboards and reports to communicate the results of data analyses to business stakeholders.
- Cross-functional Collaboration: Participate in cross team coordination with the Data Annotation, QA, and Product teams.
Requirements
- Bachelor’s Degree in Computer Science, Electrical Engineering, or related field
- Experience in SQL & Redash / Snowflake, writing complex queries
- Experience in Python and data analysis & visualization tools (pandas | plotly | seaborn)
- Strong problem-solving & communication skills
- Demonstrated experience in Computer Vision or Machine Learning is a strong plus (FYP, Coursework, Freelance or side project or industrial experience)
Benefits
- Creating a diverse and inclusive workplace
- Equal opportunity employer
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