ABOUT SYNGENTA
Syngenta Group is a $28B leading science-based agtech company, operating in more than 100 countries, with more than 50’000 employees. We are proud to stand at the forefront of the tech revolution in agriculture. Using the latest digital innovations, data, and cutting-edge technologies we want to transform the way that crops are managed and enable farmers and agronomists to enhance efficiency and sustainable food production.
Our business success reflects the quality and skill of our people. We recognize that human diversity is as important to our business as biodiversity. Embracing the unique perspectives and capabilities of our employees helps us continue to catalyze innovation, maximize performance, and create business value. Join us and help shape the future of agriculture.
Role purpose
- To collaborate and partner with key stakeholders to deliver the next generation AI, ML and Predictive analytics Model
- To work as part of an Data science team enabling the integration of data sources with next generation technologies across functional boundaries.
- Enable Power users and decision makers to solve ever more complex problems by encouraging and delivering innovative solutions that impact business outcomes.
Accountabilities
- Drive the creation of new models and capabilities that will leapfrog traditional approach based modeling and accelerate new ways of thinking
- leveraging a wide array of data from both traditional (Internal) and nontraditional (External) sources.
- Manage data analysis to develop fact-based recommendations for innovation projects.
- Mine Big Data and other unstructured data to tap untouched data sources and deliver insight into new and emerging solutions.
- Work with cross-functional teams to develop ideas and execute business plans.
- Remain current on new developments in data analytics, Big Data, predictive analytics, and technology
Critical success factors & key challenges
1. Clearly conveying the message to business on scope and risk of the problem statement
2. Completeness of the data to ensure all the essential information is covered
3. Applicability of the Big Data analysis results to meet the goals specified
4. Customer engagement and bottom line growth as the indicators of data mining success
Knowledge, experience, education & capabilities
Critical knowledge:
• Problem solving skills with the ability to design algorithms, which may include data cleaning, data mining, data clustering and pattern recognition methodologies
• Strong skills in statistical analyses with abilities in advanced data management and statistical programming using Python and R
• Proven research background, in industry work or academia, with an emphasis on delivering research that has a critical impact on multiple projects
• Provide a unique blend of skills that both unlock the insights of data and tell a fantastic story through the data Ability to use a hands on approach to integrate math, algorithms, and an understanding of human behavior to
Critical experience:
• Working Agile
• Knowledge of toolsets and capabilities utilized by expert data scientists and modelers
• NoSQL and RDBMS databases
• Data analytics and visualization
• Solid communication skills and team player
• Working with cross-functional / organizational / geography people and teams
• Have cultural awareness
• Leading the development and deployment of Machine Learning models
• Experience in Deep Learning and NLP
o Nice to have: experience in modeling business problems in areas of application like Marketing, Sales Effectiveness, Demand forecast, Churn prediction
• Tools:
o Python (Scikit Learn, Tensorflow)
o Development/Deployment in AWS
Minimum education:
• Master’s degree in informatics, computer science, data science or related fields
Syngenta Group is a $28B leading science-based agtech company, operating in more than 100 countries, with more than 50’000 employees. We are proud to stand at the forefront of the tech revolution in...
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