Job title: Data Scientist
Reporting to: Science & Innovation Manager
Hours: Two year, full-time position
The Yield is looking for a Data Scientist who is passionate about solving real world problems and providing agricultural insights through advanced analytics. The position is part of a collaboration with the University of Technology-Sydney (UTS) with the aim of predicting agricultural outcomes using cutting-edge IoT, cloud computing, and artificial intelligence technologies.
The Yield is an Internet of Things (IoT) agriculture technology company. It aims to be a global leader in intelligent solutions in the food industry. It develops IoT, cloud computing, and artificial intelligence solutions in Australia and is scaling aggressively globally.
The Yield has a highly-focused team that brings together world-leading agriculturists, scientists and technologists. It partners with global giants in technology services and has a strong commitment to open innovation and collaboration both internally and externally. Its work has been profiled in these video case studies by TechCrunch and Microsoft.
The role is an opportunity for a PhD data scientist with industry experience to work within The Yield’s data science and engineering teams. The Data Scientist will work with data sets ranging from multiyear climate data, observation data collected by on farm sensors, grower inputs, and agricultural models. The Data Scientist will be responsible for working within a multi-disciplinary team to create previously unknown insights, model and codify inherent knowledge, and provide local on farm predictions using cutting edge methods and techniques. Outcomes are focused on delivering new, valuable insights to The Yield’s customers—global food producers—and to support research innovation between UTS and The Yield.
- Developing supervised and unsupervised predictive models, algorithms, geospatial data analytics and crop models that are scalable to cloud architectures;
- Identifying and acquiring additional sources of data to deliver unique and valuable predictions to growers;
- Ensuring compliance with the systems of UTS and The Yield to protect intellectual property, digital assets, and customers’ privacy and confidential information;
- Working with collaborating groups at UTS and The Yield’s engineering and data science teams to develop solutions to release in The Yield’s products;
- Ensuring continuous improvement and development, keeping up with and leveraging new breakthroughs and advances in machine learning and AI;
- Identifying, facilitating, and contributing to opportunities for research outputs, including publications, where available.
- Contributing to a cohesive, diverse and high-performing team that is genuinely inclusive and gender-balanced;
- Establishing good relationships, communicating verbally and in writing with key stakeholders and strategically communicating outcomes publicly.
- A track record (minimum 2 years) of developing models using machine learning or AI to achieve business and commercial outcomes in areas such as environmental, climatic, geospatial, marine or agriculture modelling;
- Strong problem-solving skills with an understanding of the constraints on developing commercial solutions;
- Solid working knowledge of querying and manipulating datasets with exposure to at least one industrial strength database;
- Empathy for end-users and a creative ability to apply data and data relationships across multiple sources and domains to help solve real problems for growers and food producers;
- Strong organisational, communication and collaboration skills to build and strengthen working relationships in both academic and commercial environments;
- Ability to thrive in a dynamic and fast-paced environment of product discovery and development, working at the university/industry interface;
- Capacity to identify new opportunities and build collaborative relationships within UTS and The Yield as well as externally.
- A PhD with a strong quantitative focus.
- Experience in areas such as Statistics, Mathematics, Economics, Science, Computer Science, Environmental Science, or Agriculture Science.
- Experience in manipulating, handling and extracting data from large structured and unstructured data sets including one or more of the following: time series data, predictive atmospheric models, weather or climate data, satellite imagery, and geospatial data.
- Experience with Python (including NumPy, SciPy, scikit-learn, etc.) or proven experience of multiple other languages allowing the compression of complex data relationships into production-grade models.
To apply, please send a cover letter and CV to firstname.lastname@example.org ensuring you address the selection criteria.
This position has no closing date; applications will be reviewed as they are received.