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DATA SCIENTIST MANAGER
Data Science Manager
The Fed Beef team at JBS is seeking a data science manager who is passionate about unlocking the value of our data to provide data insights that inform and influence our product and business decisions. By managing a data science team and analyzing large internal and publicly available datasets, you will empower our business through the use of machine learning and artificial intelligence, enhance decision making and allow for insight driven collaboration.
- Leverage the latest machine and deep learning techniques to challenge our current practices in procurement, sales, marketing, operations, claims, expense, etc.
- Design, develop, and implement end-to-end machine learning production pipelines (data exploration, data preprocessing, feature engineering, model building, and performance evaluation).
- Work with different business organizations across the company to understand their needs and help identify new opportunities.
- Mentor, coach, train and manage fellow data scientists and analysts.
Successful Candidate: A successful candidate must:
- Take the initiative, easily understand the business dynamics, see the big picture, assess current practices and identify new areas where inefficiencies affect the bottom line of the company.
- Understand the uses of business and market information to better drive decisions.
- Relate with multiple teams to understand the problems of the business.
- Lead a team and managing its resources effectively.
- Have a strong analytical mindset so that they can drive decisions in a fact-based environment.
- Condense complex analysis and technical concepts with clarity and simplicity for business leaders
- Master’s or Ph.D. degree in Applied Mathematics, Computer Science, Software Engineering, Statistics, Business Analytics, Agribusiness, Accounting, Finance, Economics, etc. or equivalent experience.
- Minimum of 3 years of experience in data science with a desired knowledge of SAP, QlikView or Qlik Sense, and Business Objects.
- Highly proficient in Python, R and SQL
- Solid technical hands-on skills in machine learning (regression, classification, clustering, dimensionality reduction), deep learning (CNN, RNN/LSTM, GAN), time series data, anomaly detection, statistical algorithms, data mining, and data engineering
- Knowledge in Dash or R Shiny, Keras, TensorFlow, H2O, and cloud computing
- Strong ability to use logic and excellent problem-solving skills
- Ability to work independently and be flexible
- Ability to thrive in a fast paced, highly dynamic environment
- Demonstrated experience with agile or other rapid development methods
- Passion for innovation and “can do” attitude
- Experience in agricultural industry data science is a plus.