Senior Data Scientist
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Job Description
Senior Data Scientist responsible for implementing data models and collaborating with analytics teams at Minerva Foods in Brazil. Seeking candidates with strong experience in Python and machine learning.
Responsibilities:
- Develop and implement machine learning models (classification, regression and segmentation) using a variety of Python libraries;
- Validate machine learning models using diverse metrics and concepts such as confusion matrix, backtesting, out-of-time testing, train/test splits, cohorts, ROC-AUC and KS;
- Handle data from different sources, consolidating it into usable structures for analysis. Data may not always be in the same environment or in the ideal format for model application;
- Produce activity status updates as well as clear data process documentation to support solutions at the strategic level;
- Create storytelling and prepare presentations to communicate modeling and analysis results;
- Contribute to process changes by improving them through data to deliver measurable financial impact to the company;
- Collaborate with Data Infrastructure, Data Engineering and Systems, and Process Engineering teams to integrate analytical solutions into existing internal tools and processes as effectively as possible;
- Monitor and propose improvements in the area, targeting process enhancements related to activities, projects and initiatives to incorporate industry best practices.
Requirements:
- Bachelor's degree in STEM fields (Statistics, Computer Science, Mathematics, Physics, Engineering, etc.) or related areas;
- Minimum of 5 years of experience working on Data Science projects (Behaviour Score, Collections, Churn, Price Prediction, etc.), with demonstrable business impact;
- Required skills: Python, SQL, Machine Learning, Pandas, Scikit-learn;
- Preferred: experience with Databricks, MLOps and postgraduate degree in a STEM field;
- Plus: experience with Time Series projects;
- English - Advanced level;
Benefits:
- Availability to travel to Minerva's operations and offices for opportunity mapping, process understanding, validations and client support.
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