Syngenta is a global leader in agriculture; rooted in science and dedicated to bringing plant potential to life. Each of our 28,000 employees in more than 90 countries work together to solve one of humanity’s most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture.
Syngenta Digital is changing the agriculture industry and we want you to be part of that. Digital innovations, data and new technologies will transform the way that crops are managed in the future and enable farmers and agronomists to enhance efficiency and sustainable food production. You will help to develop solutions that turns data into meaningful information and ultimately helps to grow more food with fewer resources.
Syngenta Digital is changing the agriculture industry and we want you to be part of that.
The Syngenta Analytics and Data Sciences team is seeking a Genomics Data Scientist who will play a major role in defining, designing, experimenting, and evaluating product-focused solutions and delivering business insights utilizing data mining, machine learning methods, deep learning, computer vision and natural language processing. As a Genomics Data Scientist, you will be part of a dynamic team that supports Research and Development objectives to transform our business. As a Data Scientist, you will:
Identify viable data science opportunities and test, develop, validate, and implement end-to end analytical solutions
You will help meet the world’s most pressing needs by:
Utilizing rigorous data science approaches to help transform our Seeds product development pipeline to deliver maximum value to our growers and sustainability to agriculture
Working collaboratively on complex problems using data science to provide autonomous solutions, improve decision making and simplify our processes to deliver value to our growers
Modeling complex problems, discover and deliver insights leading to new intelligence and identify opportunities via the use of statistical, algorithmic, and visualization techniques
Job Locations available: Downers Grove or Malta, Illinois; Slater, Iowa; Raleigh-Durham, North Carolina
Create prototypes to address needs and enhance fundamental decision-making
Learn and understand the Seeds Development pipeline and operations, associated data and key decisions in order to recognize opportunities for enabling and enhancing our decision making
Research and apply the latest machine learning and deep learning methodologies to address Seeds Development challenges
Evaluate algorithm performance—validate findings using a trial and iterative approach and effectively communicate findings to technical and non-technical audiences
Identify data needs and provide recommendations; efficiently process, clean, and verify the integrity of data used for analyses
Ph.D. or Masters’ degree with equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Engineering, or related quantitative field
2+ years of experience: Deep Learning, Machine Learning, programming, data modeling and evaluation, probability and answering questions in high-dimensional datasets
2+ years of practical experience applying Deep Learning and Machine Learning to solve real-world problems or relevant quantitative and qualitative research and analytics experience
Expertise in data wrangling, mining, and modeling
Experience with SQL and AWS
Experience using a programming language (Python, C/C++, Matlab) for Machine Learning or a statistical computer language (R, Python, SQL) to manipulate data and draw insights from large data sets
Experience in Machine Learning and Deep Learning libraries such as TensorFlow, Keras, MXNet, PyTorch or Scikit-Learn
Experience with Kubernetes and Docker and the Agile Methodology
Experience with visualization and rapid prototyping tools (e.g. R Shiny, Spotfire, Power BI)
Proven interpersonal and excellent communication skills in order to communicate with stakeholders and collaborate with R&D colleagues
What We Offer:
Full Benefit Package (Medical, Dental & Vision) that starts the same day you do
401k plan with company match, Profit Sharing & Retirement Savings Contribution
Paid Vacation, 12 Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts among others
A culture that promotes work/life balance, celebrates diversity and offers numerous family-oriented events throughout the year
Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.
Syngenta is one of the world’s leading agriculture companies, comprising of Syngenta Crop Protection and Syngenta Seeds. Our ambition is to help safely feed the world while taking care of the planet. We aim to improve the sustainability, quality, and safety of agriculture with world-class science and innovative crop solutions. Our technologies enable millions of farmers around the world to make better use of limited agricultural resources. Syngenta Crop Protection and Syngenta Seeds are part of Syngenta Group. In more than 100 countries we are working to transform how crops are grown. Through partnerships, collaboration, and The Good Growth Plan we are committed to accelerating innovation for farmers and nature, striving for carbon-neutral agriculture, helping people stay safe and healthy, and partnering for impact.To learn more visit www.syngenta.com and www.goodgrowthplan.com. Follow us on Twitter at www.twitter.com/Syngenta and www.twitter.com/SyngentaUS.We are