Data Scientist - Quantitative Genetic Applications (m/f/d)

Beschreibung

About KWS

KWS is one of the world’s leading plant breeding companies. With the tradition of family ownership, KWS has operated independently for more than 165 years. It focuses on plant breeding and the production and sale of seed for corn, sugar beet, cereals, potato, rapeseed, sunflowers and vegetables. KWS uses leading-edge plant breeding methods. Around 6.000 employees represent KWS in more than 70 countries. For more information: www.kws.com/career. Follow us on LinkedIn® at https://linkedin.com/company/kwsgroup/.

Data Scientist for the Development of Quantitative Genetic Applications (all gender)

Field of Work: Research & Development
Location: Einbeck, Lower Saxony, DE
ID: 8545

Statistical modeling is your passion, and you want to bring the research of a leading company forward? Then start with us as Data Scientist (all gender) for tool development for quantitative genetics within the Biostatistics team of KWS SAAT SE & Co. KGaA, in full-time and for an unlimited period, at our headquarter in Einbeck. In a well-rehearsed team, the possibility to work remotely from Germany is given based on arrangement.
In this role, you can expect to be involved in biostatistical projects focused on tool development for instance for molecular diversity assessment, genomic prediction, or genome wide association mapping. Many projects involve combining phenotypic and molecular marker data to get a deeper understanding of the role of genetics in phenotypes of field crops.You will be responsible for

• Maintain and extend the existing tool landscape for analyzing phenotypic and molecular data
• Benchmark and validate new methods based on simulations and empirical data before productive implementation
• Develop and optimize data analysis tools for use in marker-assisted breeding schemes for all crops
• Initiate and manage projects to identify and implement cutting-edge statistical methods
• Optimization of performance and efficiency of tools for processing of large datasets
• Provide statistical support and conduct data science projects in all areas of KWS
• Monitor scientific literature and patent applications

You bring in your strength

• University degree in quantitative/ population genetics with focus on data analysis and statistics, mathematics or similar qualification
• Strong background in R or Python programming
• Experience in statistical modeling (linear mixed models, multivariate parametric and non-parametric methods),
• Passion for data analysis and the ability to handle large data sets
• Excellent team player and good communication skills
• Professional written and verbal communication skills in English

This would be a plus

• C++ as well as Knowledge related to basic Linux system administration and BASH
• Bayesian statistics
• Good knowledge of the Git version control system and continuous integration / deployment
• Interest in biological questions, exposure to plant breeding/ genetics
• Familiarity of working on a High-Performance Computing Cluster
• Additional German language skills

That is our offer to you

• In this role you will work close together with the scientific and IT area of KWS, so you have the chance combine both worlds and advantages.
• As a family-run company we are guided by the values of team spirit, proximity and trust, independence, and vision; this culture is lived in practice creating thus an open and friendly working atmosphere.
• We offer excellent work equipment (e.g. ergonomic workstations, several monitors, air conditioning, high-end technical equipment), a fully-fledged, subsidized canteen and sufficient free parking spaces at the office.
• In a well-rehearsed team, the possibility to work remotely from Germany is given based on arrangement. Additionally, we offer capital formation benefits, Christmas and holiday bonuses, childcare allowance and a job bike.
• True to our motto Make yourself grow, we support employees’ professional and personal development.
• Health & Safety are very important for us: our company doctor, company fire brigade / paramedics (with time credit) and company sports create a solid base for this.