Chief Data Modeller

Há 3 dias

São Paulo, São Paulo, Brasil beBeeDataAnalytics Tempo inteiro R$1.000.000 - R$1.400.000

Our company seeks an exceptional professional to lead our Data Analytics and Predictive Science team in Brazil.

The successful candidate will be responsible for developing and implementing advanced data analytics and predictive modelling techniques to support the development of innovative crop protection products.

The ideal candidate will have a strong academic background in statistics and predictive modelling, as well as experience working with data-science, analytics, and modelling tooling. They will also possess scientific domain knowledge in agronomy, biology, chemistry, or a related field.

The role involves collaborating with cross-functional teams, including product biologists, chemists, and other data scientists to drive business initiatives and develop models that inform decision-making.

Key responsibilities include:

  • Developing and implementing data-driven solutions to improve crop yields and reduce environmental impact.
  • Collaborating with internal stakeholders to identify opportunities for standardized improvements in protocol and experimental design, data quality, and reporting.
  • Working with colleagues in adjacent fields of data analytics and predictive science to investigate interdisciplinary and multiscale modelling approaches to solve fundamental challenges in active ingredient development for crop protection.
  • Providing expertise and guidance to scientists in the design of experiments and field trials for modelling purposes.

Successful candidates will have:

  • A strong academic foundation in statistics and predictive modelling to postgraduate level or natural science PhD.
  • Knowledge of relevant data-science, analytics, and modelling tooling (e.g., Python, R, Matlab).
  • Scientific domain knowledge in relevant fields such as agronomy, biology, chemistry, etc.
  • Experience in developing models relevant to biological or crop protection outcomes.
  • Excellent communication skills to communicate complex data concepts to specialist and non-specialist audiences.

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