drjobs Head Applied Data Genetics Science Seeds Field Crops Europe MW

Head Applied Data Genetics Science Seeds Field Crops Europe MW

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1 Vacancy
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Job Location drjobs

Budapest - Hungary

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Reporting to Head Europe you lead the Applied Data Genetics Sciences teams to ensure successful data management delivery of highquality data analytics and build operations research capabilities to improve Seeds Dev technical operational and planning decision making in Corn Sunflower Cereals and WOSR businesses.

The position is offered on a permanent contract based in France/Saint Sauveur (31) or Germany/Bad Salzuflen or Hungary/Mezotur or Budapest or flexible in another location on a SYNGENTA site in Europe.

Some level of business travel required (mostly EAME workshop meeting visits).

Starting date: Q4 2024

Accountabilities

Data Science Leadership: Oversee overall data science analytics and Applied Genetic Sciences strategy in Europe field crop Seeds Development; ensure proper support to all functions to deliver pipeline needs focused on business value. Understand key businesses and financial parameters and their impact.

Innovation Catalyst: Drive novel strategies and inspire a shift in behaviors and mindset to realize the full value of data and analytics and achieve the objectives required to deliver the EUROPE pipeline and agronomy solutions of the future.

Multidisciplinary Team Leadership: Lead a team of genomic phenotypic and operations research data science engineers to ensure the best use of data and technology to facilitate decision making. Set evaluation priorities role modeling of Syngenta values with a focus on people development.

End to End Solution Deployment: Identify and define challenges drive ideation build requirements develop models and deploy products/tools iteratively through MVP (minimum viable product) delivery in order to successfully implement data driven solutions covering descriptive predictive and prescriptive analytics for corn oilseed and cereal crops in EUROPE.

Global Collaboration: Work alongside global teams to help translate regional needs into the development of analytics driven workflows to help the organization make improved datadriven decisions at scale following global data science best practices.

Crossfunctional Alignment: Maintain strong interaction and collaboration with global analytics & data science IT and portfolio teams to ensure transparency alignment and implementation of new enterprise technologies and analytical methodologies; providing mitigation and transparency when alignment is not possible or has been broken. Facilitate planning of resources and building capabilities to deploy and implement new technologies equipment and personnel for effective and efficient functioning of all Data Science and analytic activities across the region.

Change Leadership: Lead through influence and change to create an integrated applied data science team supporting all Seeds Dev operations.
Working in a team/collaborative environment in Europe to deliver optimal predictive breeding information to support E2E advancement process in all field crops and respective Market segments.

Quantitative genetics and Genomic selection Innovation : Enable R&D capabilities and their team development including planning supporting and contributing to efficient growth capacity and capability building and critical mass in European predictive breeding team structure and processes.

Ensuring most valuable predictive breeding methodologies are implemented and ensuring the leveraging best practices share leverage harmonization across different crops.

Scouting new innovative breeding approaches review and propose potential plan for implementation always by measuring the impact of different options into the genetic gain.

Active contribution to Global and/or regional scientific project following regional Crop Priorities.

Strong collaboration with Germplasm Development Heads and their teams to provide innovative and strategic recommendation in the area of interest.

Establish and embed new ways of working for both Data and Applied Genetic Sciences teams and interdependencies with relevant Europe and Global Seeds Dev functions.


Qualifications :

PhD in Plant Breeding/Quantitative Genetics Crop Science Data Science Computer Science or relevant experience with more than 10 years experience in a global research and development environment including 5 years leading data science and Applied Genetics Sciences operations.

Strong expert in Quantitative genetics and Genomic selection: solid knowledge of plant breeding and genetics principles and application practices methods of analysis scenario planning.

Experience working successfully in international and multidisciplinary project team environment.

Track record of managing teams and developing talent leads individuals through complex situations. Proven leadership skills and ability to work collaboratively with crossfunctional teams to effectively achieve business results.

Strong analytical mindset and Agile project management implementation including planning budget management and operational excellence.

Demonstrated abilities to develop project plans analyze and interpret data.
Ability to perform successfully in a fastpaced dynamic teambased environment. Manages multiple projects and priorities from different stakeholders across disciplines and cultures and across geographies.

Strong capabilities to communicate with technical and nontechnical audiences and work effectively with all management levels in a multicultural organization.

Professional English required to work in our multicultural organization (meetings emails documents).

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.

 


Remote Work :

No


Employment Type :

Fulltime

Employment Type

Full-time

Company Industry

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