DS104-ESG-Tech Prof - Data Science, Sr
Rio de Janeiro, RJ, BR, 291941
We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry.
A Senior Data Scientist leads project tasks or small projects to perform data engineering, data modeling or model deployment. This role works independently with subject matter experts to obtain data from different sources, complete data clean up and build a data dictionary independently. This role is able to build models independently and implement the model deployment process using off-the-shelf solutions or with assistance from a developer. This role starts to contribute to and shape the group strategy and identifies opportunities for process improvement. This role co-authors publications and patents and starts to participate in industry events. Completion of an undergraduate degree in STEM and 4+ years of related experience is required. Master's degree in STEM is preferred.
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location
Rua Paulo Emidio Barbosa 485 Q, Rio de Janeiro, Rio de Janeiro, 291941, Brazil
Job Details
Requisition Number: 182988
Experience Level: Experienced Hire
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Additional Locations for this position:
Compensation Information
Compensation is competitive and commensurate with experience.
Job Segment:
Data Modeler, Business Process, Database, Data, Management, Technology