Sr Data Scientist

Project Description: The candidate must have experience and fundamental knowledge in machine learning experience in deploying models and programming skills to develop and deliver novel solutions in an industry setting.

Responsibilities: Partner with R&D scientists to develop and prototype rigorous machine learning solutions aligned to project needs

• Design and implement scalable data pipelines for processing highcomplexity datasets such as highthroughput bioassays or largescale agriculture datasets
• Partner with data scientists data engineers and production teams to deploy and maintain data products at scale
• Communicate and train research partners on models and products to facilitate datadriven decisions
• Communicate insights derived from complex data analysis into simple conclusions that empower leadership to drive action; communicate results in internal and external forums; and contribute to scientific articles as needed
• Steward data product life cycle and partner with other scientists to continuously improve underlying models and optimize data architecture
• Stay abreast of emerging technologies in big data machine learning and agriculture tech and advocate for their adoption where beneficial

Required Qualifications

• 78 Years of strong expertise in R or Python programming languages and their application to data wrangling machine learning (e.g. TensorFlow PyTorch) and data visualization
• Experience and fundamental understanding of machine learning techniques (e.g. logistic regression random forest XGBoost SVMs Kmeans neural networks)
• Solid understanding of variable selection; dimensionality reduction; model diagnostics; and model training testing and validation
• Experience deploying machine learning models in production (e.g. CI/CD pipeline development; containerization using tools such as docker podman or Kubernetes; Git)
• Ability to work both independently and within a multidisciplinary team environment to provide innovative solutions
• Ability to successfully collaborate with colleagues from diverse technical backgrounds which includes excellent communication interpersonal verbal and written skills
• Strong critical thinking and problemsolving skills flexibility and willingness to learn

Preferred Qualifications:

• Familiarity with modeling biological cellular or ecological data; molecular biology or biochemistry concepts; or data science in agriculture
• Proven experience as a machine learning engineering or similar role with a strong focus on machine learning deployment and data pipeline construction
• Familiarity with artificial intelligence or generative AI techniques
• Experience in big data technologies (e.g. Hadoop Spark) and database management systems (e.g. SQL NoSQL)
• Experience with AWS
• Experience consulting on scientific projects or working within a scientific team