Senior Finance Data Scientist with Artificial Intelligence Expertise

hace 1 día


Zaragoza, Zaragoza, España Matchatalent A tiempo completo
About the Company

Our client is a leading player in the exploration, production, transportation, and sale of crude oil and natural gas.

The company operates through three main segments: Upstream, Downstream, and Corporate. The Upstream segment focuses on crude oil, natural gas, and natural gas liquids exploration, field development, and production. The Downstream segment is responsible for refining, logistics, power generation, and the marketing of crude oil, petroleum, and petrochemical products to international and domestic customers. The Corporate segment provides supporting services, including human resources, finance, and information technology.

Job Summary

We are seeking a seasoned Business System Analyst to join our Digital Solutions & Data Management Division of the Digital Finance Department.

The Digital Finance Department is responsible for the coordination, development, and management of information systems used in financial accounting, treasury, financial planning & forecasting, performance management, and digital solutions for the Finance Business line.

The Digital Implementation Division provides program management services for implementation, rollout, and support of finance system solutions through digital technologies, including advanced analytics, Robotic Process Automation (RPA), and Artificial Intelligence solutions.

Responsibilities
  1. Design, develop, and implement AI-powered solutions to automate tasks, improve processes, and support data-driven decisions across Financial Accounting, Treasury, Performance Management, and Investor Relations.
  2. Collaborate closely with business stakeholders to understand their needs, translate them into technical requirements, and deliver impactful solutions.
  3. Assess Finance AI use cases, evaluate options, and support implementation.
  4. Develop and manage machine learning models for financial forecasting, fraud detection, risk assessment, and more.
  5. Clean, transform, and analyze large datasets from diverse sources to ensure data quality and suitability for modeling.


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