Looking for an experienced Data Science Consultant for Latin America to meet client needs. We are looking for team members who can utilize advanced analytics and toolsets to deliver key projects for our engagement. Apply today!

The Role

Support and maintain LATAM work using advanced analytics tools in a CI/CD environment.
Collaborate with data engineers and ML engineers to gain a deep understanding of data and models.
Utilize big data technologies to efficiently process data and construct scalable data pipelines, spanning from batch to real-time processing.
Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines, leveraging the powerful NGAA platform on Azure.
Manage cloud alerts, monitors, dashboards, and troubleshoot machine learning infrastructure effectively.
Ensure the accuracy of implemented forecasting solutions and continuously enhance the forecast accuracy.
Conduct root cause analysis of demand issues and propose experimental approaches for solutions.
Foster prompt and transparent communication with the business team and team members located in other areas.

The Person

A minimum of 8 years of overall experience, including at least 5 years of hands-on work in data science and machine learning.
Proficient in DevOps and machine learning, with practical experience using one or more cloud service providers (preferably Azure).
Bachelor's degree in Computer Science, Mathematics, Physics, or a related technical field.
Strong understanding of demand planning and management activities, including seasonal adjustments, promotions, discounts, and other relevant factors that influence forecasting.
Skilled in developing both supervised and unsupervised machine learning models.
Proficiency in statistical programming languages such as Python and R, as well as database query languages like SQL.
Knowledgeable in statistical tests, distributions, regression, and maximum likelihood estimators.
Desirable experience with Databricks and ADF. Familiarity with Spark, Hive, and Pig is an added advantage.
Experience with version control systems like GitHub and continuous integration/continuous deployment (CI/CD) tools.
Knowledge of ML Ops DevOps and deploying ML models is required. Preferred experience using ML, Flow, Kubeflow, etc.

Our client is an equal opportunity employer, and we celebrate diversity and are committed to creating an inclusive environment for all.

Note: This job description is intended to convey information essential to understanding the scope of the position and is not an exhaustive list of skills, efforts, duties, responsibilities, or working conditions associated with it.

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