Bayer

Data Scientist-Environmental

Job description

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.


Data Scientist-Environmental


Why Bayer?

“Health for all and Hunger for none” is our mission at Bayer. Every day, we are privileged to work on purposeful cutting-edge projects to bring our mission to life. Join us at Bayer to have a career that you can put your passion into practice and make an impact using Science for a better life.


For our newly established IT Hub, we are looking for:


Data Scientist – Environmental and Agronomic Modeling


You will be responsible for:


  • Build an analytics-driven product pipeline
  • Develop and deploy new solutions based on predictive and prescriptive modeling utilizing a wide range of field observations and environmental data (weather, soil, remote imagery), to improve field operations and enable better decision making.
  • Building cross-functional relationships with the business and effectively connecting within the Data Science Community
  • Using advanced mathematical models, machine learning algorithms, operations research techniques, and strong business expertise deliver actionable insights
  • Develop sustainable, consumable, accurate, and impactful reporting on model inputs, model outputs, observed outputs, business impact, and key performance indicators.
  • Presenting crucial narrative to peers, senior management, and internal customers in order to create strategic and operational changes in business

We would expect from you:


  • Masters degree with 2+ years of experience or PhD
  • Educational preparation or applied experience in at least one of the following areas: Machine Learning, Computer Science, Mathematics, Statistics or other closely related quantitative discipline. Candidates with demonstrated experience in applying machine learning to environmental modeling, crop modeling, epidemiology, or other modeling and interpretation of found, open systems data preferred (but not required).
  • Strong programming experience in Python, R, or another high-level programming language, ideally with working with machine learning and statistical modules/ packages. Demonstrated experience in reinforcement learning a plus.
  • Strong computer development skills, with demonstrated experience in collaborative coding and version control (GIT) and ability to write clear, well commented, and organized code.
  • Experience in Agile project management and/ or willingness to learn
  • Experience in building models, including data extraction and cleaning, feature selection and engineering, and model selection/ validation
  • Strong sense of ownership to deliver valuable analysis through acquisition and application of domain knowledge; motivated to develop and work from a strong understanding of our business and the science required to execute it.
  • Strong communication competencies to include presentations and delivery of complex quantitative analyses in a clear, concise, and actionable manner to extended team and small groups of key stakeholders.
  • Working on new machine learning methods e.g. Bayesian Methods, GCN, Spherical CNNs, GAN, Unsupervised Learning, Distributed Learning and others) and methods for gaining insights from these models (shapely, partial dependence, etc.)
  • Design and implementation of artificial neural networks
  • Working closely with product management to define product strategy and roadmap
  • Creation of innovative products supported by prototypes, scientific publications, and patent applications

In the exchange we will offer you:

  • A flexible hybrid work model
  • Career development, 360° Feedback & Mentoring programme
  • Wide access to professional development tools, trainings, & conferences
  • Competitive salary, annual bonus & top performers awards
  • VIP Medical Care Package (including Dental & Mental health)
  • Pension plan
  • Holiday allowance (“Wczasy pod gruszą”)
  • Life & Travel Insurance
  • Co-financed sport card with unlimited usage
  • Meals Subsidy in Office
  • Home Office Setup & Maintenance allowance
  • New & exciting open office space coming in Spring ‘22

Our inclusive culture at Bayer:


Bayer is an equal opportunity employer. We care about inclusion in terms of gender, age, race, skin color, nationality, religion, marital status, sexual orientation, background, physical or mental disabilities and on every other grounds. Applying for our position, we assure you that we will assess your application solely on the basis of your competencies.



YOUR APPLICATION



Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

Bayer offers the possibility of working in a hybrid model. We know how important work-life balance is, so our employees can work from home, from the office or combine both work environments. The possibilities of using the hybrid model are each time discussed with the manager.




Location:
Poland : Mazowieckie : Warszawa

Division:
Enabling Functions

Reference Code:
505141


Location:

Poland : Mazowieckie : Warszawa


Division:

Enabling Functions


Reference Code:

505141

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