Head of Data Science

The Swiss product company which offers compelling digital agronomy solutions for B2B clients and large farming businesses is looking for a Head of Data Science who will be involved in the development and commercial deployment of Data Science-driven solutions for Smart Farming. You will provide leadership, training and technological support for a team of talented data scientists in a challenging and rewarding start-up environment. ​Strong commercial delivery focus.

Head of Data Science
Full-time
English: Upper-intermediate

Responsibilities:

  • 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

Benefits:

  • 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
Our recruiter
Марта Стопец
Марта Стопец
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