Associate DS AI Factory

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BBVA is a global company with more than 160 years of history that operates in more than 25 countries where we serve more than 80 million customers. We are more than 121,000 professionals working in multidisciplinary teams with profiles as diverse as financiers, legal experts, data scientists, developers, engineers and designers.

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We’re a group of people with a passion for cutting edge technology, mutual learning and innovative problem solving. We strive to bring the opportunities that Artificial Intelligence offers to the financial industry.

As an Associate Data Scientist joining AI Factory, you become a crucial part of a team that is pushing the boundaries of Artificial Intelligence in the financial sector. Your role involves assisting in the execution of key projects within the DATA area, contributing to our strategic goals under the guidance of more experienced team members. Your foundational understanding of mathematics, analytics, and statistics will be put to use in a real-world business setting, where you will be actively engaged with cross-functional teams. This engagement will provide you with the opportunity to offer analytical support and insights, aiding in the identification of new business opportunities. We are committed to your continuous learning and professional development in the field of data science and related areas. Adhering to governance standards and best practices in Advanced Analytics to ensure the reliability and accuracy of your work will be a key responsibility in your role at AI Factory.

About the job:

• Foundational Machine Learning Knowledge: Solid understanding of basic machine learning algorithms and principles, with an eagerness to learn and apply more advanced techniques as part of a team.

• Data Science Fundamentals: Good grasp of statistics, basic machine learning concepts, data visualization, and an understanding of big data technologies. Familiarity with data science tools and libraries in Python (such as Pandas, Scikit-learn).

• Programming Skills: Proficient in scripting and programming with Python. Openness to learning other programming languages as needed, and beginning experience with Spark or similar big data processing frameworks.

• Version Control Systems: Basic knowledge of version control systems like Git, with the willingness to develop more advanced skills in collaboration and code management.

• Database Management: Skills in SQL for data extraction from relational databases. An introductory understanding of non-relational databases and distributed database systems is a plus.

• Data Cleaning and Preprocessing: Ability to perform data extraction, cleaning, and transformation, with an understanding of ETL processes and tools.

• Interest in AI and Technology Trends: A keen interest in emerging AI technologies and data science trends, with a motivation to learn and apply these in practical scenarios.

• Applied Learning Approach: Some experience or projects demonstrating the application of machine learning models to real-world problems, even at a basic level.

• Cloud Computing Basics: Understanding of cloud computing fundamentals, with exposure to services from providers like AWS, Google Cloud, or Azure.

• Ethical AI Awareness: Awareness of ethical AI principles and data privacy considerations, with an understanding of their importance in data science work.

• Communication Skills: Good communication skills, capable of explaining data science concepts and findings in a clear and understandable manner.

Team Collaboration: Ability to work effectively as part of a data science team, contributing to project goals and learning from more experienced colleagues.

Skills:

Algorithm Analysis, Algorithms, Analytical Models, Azure Machine Learning Studio, Computational Algorithms, Data Algorithms, Data Analysis Management, Data Analytics, Deep Learning Algorithms, Machine Learning Algorithms, Machine Learning Model Management, Mathematical Algorithms