Equifax is looking for a Data Scientist to join their Data Science team in Iberia. The ideal candidate for this role has strong analytical skills and is keen to work in innovation projects, contributing to generate new NPI for Equifax Iberia and its clients.

This is an excellent opportunity to develop a professional career in an international environment, working with cut-off cloud tools and collaborating with senior analytics professionals.

What you will do

Utilize combined knowledge of data structures, analytic algorithms/models and strong

computer science fundamentals to prepare datasets, conduct analytics, and develop

deployable solutions with guidance from more senior resources.

Leverage knowledge of data structures and algorithms to run complex data analysis.

Able to analyze and prepare complex and new data sources and incorporate them into

analytical solutions.

Research new methodologies and their applications in current and future process and business lines.

Works on moderate complexity tasks in problems often within multiple business or

analytical domains, collaborating with other teams to develop predictive models, risk.

assessments, fraud detection, recommendation engines, etc.

Package, summarize and visualize analytical findings and results for management.

Evaluate the work of peer and/or junior data scientists to ensure high quality solutions.

What experience you need

BS degree, preferably in mathematics, statistics or equivalent discipline.

At least 4 years of experience in a related analytical role, including experience with the design and development of predictive models

Cloud certification strongly preferred.

Technical capabilities including Python (required), SQL (required), BigQuery, GCP, R, MS Excel / Google Sheets, Vertex AI, TensorFlow, Gemini, Hugging Face, Airflow.

Languages: High proficiency in both English and Spanish are required.

​What could set you apart

Artificial Intelligence & Generative AI - Utilize artificial intelligence and generative AI to improve process efficiency, effectiveness and products.Collaboration - work collaboratively across different projects, communicating technical details to technical and non-technical stakeholders. Manage own priorities within and across teams.Consultancy Business Acumen - Have a good understanding of business and operational processes, related market segments and technical intricacies to identify how analytical solutions can cover a commercial/business problem.Decision Modeling - Understand advanced statistical concepts used to contribute to the development of stress tested deployable machine learning algorithms (Logistic Regression, Xgboost, Neural Networks, etc.).Leadership and Teamwork - Participate in a collaborative and productive team environment and take charge of technical and self development.Problem Solving - Utilize hypothesis based problem solving to deliver pragmatic resolutions to business problems. Statistical Programming - Execute and contribute to version controlled code and make use-case-specific modifications as needed. Manipulate and work with unstructured/structured, small and big data.

Primary Location:

ESP-Madrid Castellana

Function:

Function - Data and Analytics

Schedule:

Full time