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Applied Genetics Lead- Pipeline Data Science

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Job Title: Applied Genetics Lead- Pipeline Data Science
Location: Durham, NC, South United States, USA
Company: Syngenta
Industry Sector: Agribusiness
Industry Type: Plant & Soil Sciences, Seed & Biotechnology
Career Type: Researcher/Research & Development
Job Type: Full Time
Minimum Years Experience Required: N/A
Salary: Competitive
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About Syngenta

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.


About Us

We invite you to help us shape the future of agriculture. At Syngenta, we believe every employee has a role to play in safely feeding the world and taking care of our planet. To support that challenge, we are currently seeking an Applied Genetics Lead – Pipeline Data Science in Durham, NC. Other Syngenta locations might be considered. In this role, you will collaborate closely with our teams around the globe with emphasis on:

    Leading data science projects to optimize breeding pipeline processes and strategies Leading data science projects to maximize genomic selection outcomes Applying novel methods to derive insights at the breeding program and crop unit level for pipeline optimization and intelligence


    Lead the design, analysis and execution of exploratory studies focusing on driving optimal breeding pipeline decisions, improving breeding strategies and processes, implementing new breeding methodologies, and maximizing genomic prediction accuracy to accelerate genetic gain. Derive novel breeding pipeline insights from complex datasets through the application of machine learning, predictive, statistical, simulation, and/or other computational approaches Collaborate closely with Germplasm Development teams to formulate hypotheses, test, and validate findings of pipeline simulation studies in targeted production environments Drive tangible actions and improvements in breeding schemes and process and work closely with Germplasm Development teams towards preparation of transition plans and implementation of improved breeding schemes. Partner with Market Segment teams to assess and deploy portfolio modeling tools and contribute to analytical methods used for late-stage germplasm evaluation and advancement decisions. Deploy novel analytical methods and contribute to development of new tools and user interfaces for optimization of breeding decisions, pipeline insights and intelligence in close partnership with Analytics & Data Science and IT teams Consistently document and communicate research outcomes to ensure strategic forward planning and rigorous application in breeding pipelines Keep up to date with internal and external advances in data science toolbox, predictive analytics methodologies, as well as relevant emerging science and technology topics. Coach/mentor direct reports when applicable and extended team members in areas of technical expertise and contribute towards employee development on day-to-day basis. Participate in recruiting or people initiatives as appropriate.


    Ph.D. in Data Science, Biostatistics, Quantitative Genetics, Statistical Genetics, or relevant field Minimum of 3-5 years of experience in R&D setting Understanding of plant or animal breeding and quantitate genetics theory Fluency in open-source programming languages Experience with large, complex datasets encompassing structured or unstructured sources and diverse phenotypic, genotypic, or environmental data and use of data mining algorithms Experience with stochastic simulations for pipeline optimization Experience developing and/or deploying statistical modelling and machine learning Demonstrated creativity, scientific curiosity, and problem-solving ability Strong initiative coupled with continuous learning and growth mindset Ability to collaborative effectively and deliver outstanding results as part of global and cross-disciplinary teams Strong communication skills, ability to influence and drive change

Preferred Requirements

    Prior experience in seeds industry R&D setting Practical knowledge and understanding of commercial plant breeding programs Knowledge of R and Python programing Experience developing user interfaces Experience with cloud computing applications, API environments and visualization platforms

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.


Family and Medical Leave Act FMLA


Equal Employment Opportunity Commission's EEOC


Employee Polygraph Protection Act EPPA



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Job Post Date: 09/17/21
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