Syngenta | Product Placement Data Science Intern | Malta, IL | United States | BigDataKB.com | 2022/10/30

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Job Location: Malta, IL

Company Description

Syngenta Seeds is one of the world’s largest developers and producers of seed for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve the quality and yields of crops. High-quality seeds ensure better and more productive crops, which is why farmers invest in them. Advanced seeds help mitigate risks such as disease and drought and allow farmers to grow food using less land, less water and fewer inputs. Syngenta Seeds brings farmers more vigorous, stronger, resistant plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions. Syngenta Seeds is headquartered in the United States.

About This Job

Job Description

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, the Product Placement Team is currently seeking a Data Scientist in Malta, IL. As a Product Placement Data Scientist, you will assist in developing workflows to analysis early season plot quality metrics.

Work With Us And You’ll Get

As an intern at Syngenta, you have the opportunity to work alongside some of the brightest minds in the industry, and work on real projects finding real solutions.

  • Competitive wages
  • Ongoing career development resources
  • The opportunity to work on meaningful, innovative projects that solve problems
  • A culture that celebrates diversity & inclusion, promotes professional development, and offers flexible work options to meet both your work and personal needs

Projects pursued during the internship can be flexible to highlight the experience and expertise of the applicant.

Estimated Duration: May 2023 – August 2023

You Will

  • Collaborate closely with a multi-disciplinary team of plant breeders & data scientists in analytical activities required for maintaining an active corn or soy discovery breeding program
  • Gather and transform and structure large datasets for genetic or statistical analysis
  • Integrate multiple data types (environmental, GIS, performance data, etc.) to deliver predictive and prescriptive insights
  • Expand existing analytical methodologies and identify novel solutions that balance theory and the practicalities of working at industrial scale
  • Engage with stakeholders to communicate key results
  • Operate in accordance with Syngenta Health, Safety, & Environmental (HSE) standards

Qualifications

What you must have:

  • Enrollment in a M.S. or Ph.D. in Data Science, Computer Science, Quantitative Genetics, Population Genetics, Agronomy, Statistics, Genomics, Animal or Plant Breeding, or related field

What You Might Also Contribute To The Team

  • Demonstrated proficiency in one or more modern programming languages (Python, R etc.)
  • Familiarity with Linux shell scripting in a cloud environment is a plus
  • Scientific curiosity and passion for creative problem solving
  • Ability to communicate complex ideas and results in a clear and actionable manner
  • Exceptional interpersonal skills, comfortable working independently and as part of a team
  • Proactive approach to assigned objectives and goals
  • Prior data cleaning and management experience is strongly desired

Additional Information

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, gender identity, marital or veteran status, disability, or any other legally protected status.

Family and Medical Leave Act (FMLA)

(http://www.dol.gov/whd/regs/compliance/posters/fmla.htm)

Equal Employment Opportunity Commission’s (EEOC)

(http://webapps.dol.gov/elaws/firststep/poster_direct.htm)

Employee Polygraph Protection Act (EPPA)

(http://www.dol.gov/whd/regs/compliance/posters/eppa.htm)




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