GEP is a diverse, creative team of people passionate about procurement. We invest ourselves entirely in our client’s success, creating strong collaborative relationships that deliver extraordinary value year after year. Our clients include market global leaders with far-flung international operations, Fortune 500 and Global 2000 enterprises, leading government and public institutions. 

We deliver practical, effective services and software that enable procurement leaders to maximise their impact on business operations, strategy and financial performance. That’s just some of the things that we do in our quest to build a beautiful company, enjoy the journey and make a difference. GEP is a place where individuality is prized, and talent respected. We’re focused on what is real and effective. GEP is where good ideas and great people are recognized, results matter, and ability and hard work drive achievements. We’re a learning organization, actively looking for people to help shape, grow and continually improve us.

Are you one of us?

GEP is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, national origin, religion, sex, disability status, or any other characteristics protected by law. We are committed to hiring and valuing a global diverse work team.

For more information please visit us on GEP.com or check us out on LinkedIn.com.

As a Data Scientist, you will play a pivotal role in establishing patterns of the time series-based data we provide. You will leverage your expertise in data analysis, statistical modeling, and machine learning to develop methodologies that enhance the accuracy and reliability of our indexes and prices. Responsibilities include:
- Analyzing large volumes of time series data to identify trends, anomalies, and patterns;
- Developing and implementing statistical models and algorithms to improve data quality and support data-driven decision-making;
- Collaborating with cross-functional teams to understand business requirements and translate them into actionable insights;
- Staying abreast of advancements in data science techniques and technologies to continuously improve our methodologies.

Education: Graduation in a relevant field such as Data Science, Statistics, Mathematics, Physics or a related quantitative discipline. An academic background with coursework in statistics, machine learning, and data analysis is desirable.

Desirable Skills:
- Proficiency in R programming language, or SQL/Python for data analysis and modeling;
- Deep understanding of statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and predictive modeling. Experience with machine learning frameworks and deep learning techniques is a plus;
- Strong problem-solving and analytical skills, with the ability to translate complex data into actionable insights.

Credentials/Differentiators:
- Previous experience in a data science role;
- Publications or contributions to the data science community;
- Certifications in data science, machine learning, or related fields.