- Manage delivery, technical enablement and methodology adoption in tight
- Collaboration with Gamaya software and hardware teams and business stakeholders
- Drive and adjust DS roadmap based on business needs, capabilities and Gamaya business strategy
- Support DS projects with senior skills and expertise. Trigger respective content deep dives to ensure the best practice approach and outstanding quality of the solution
- Identify gaps with respect to DS capabilities and skills. Pro-active solution finding and drive respective implementation
- Develop, and manage the delivery of, DS project portfolio according to priorities.
- Strong collaboration spirit in an agile team environment
- Establish common practices for the development of Data Science for Remote Sensing (DS4RS) methods and solutions.
- Engage with senior business leaders to widen understanding of DS4RS potential and risks, and related business opportunities
- Identify relevant industry/technology trends, engage with externals partners/research.
- Act as a role model and "go-to-person" in respect of skills and experience
Must have, technical skills:
- programming skills in Python, with TensorFlow/PyTorch
- Google cloud platform or similar cloud infrastructure, data version control tool, and dynamic data repositories implementation
- Supervised learning methods: sparse linear regression, kernel methods, SVM, neural networks, CNN, RNN, model selection
- Unsupervised learning methods: k means, hierarchical clustering, outlier detection, gmm, density estimation, PCA, ICA, VAE, GAN
- Experience with Image processing: segmentation, denoising, inpainting, super-resolution.
- Experience with time series: classification, switch point detection, forecast, anomaly detection.
Nice to have:
- Proven publication record in international conferences and journals (e.g., NIPS, ICML, AISTATS, MICCAI, CVPR, ICPR)
- Advanced probabilistic modeling: tensorflow_probability/pymc3, normalizing flows, multiview learning
- Experience with preemptible training workflow in the cloud with Kubernetes with GCP or similarly Azure/AWS
- Computational analysis of algorithms, distributed computing with tf. distribute or similar tool
- Experience with optimization: first-order methods: gradient descent, proximal methods, stochastic gradient descent flavors, variational inference.
- Experience with the agribusiness
Must have, experience:
- Ph.D. in Computer Science, Electric Engineering, Applied Mathematics, Physics or similar, with a focus on statistical analysis and machine learning
- 2+ years of postdoctoral handling a variety of real-world datasets and coding his/her own analysis algorithms or
- 4-5 years of professional experience working in data science, handling a variety of real-world datasets and coding his/her own analysis algorithms
- Work with a great team of bright scientists and engineers
- Be a part of the sustainable future of agriculture
- Enjoy the dynamic and international environment
- Compensation above the market