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Data Scientist - Edge Computing

Our client is one of the leading provider of edge computing software, specifically for industrial IoT applications. The platform is powered by advanced machine learning to enable real time analytics on the edge. Some industries their product is aligned with include manufacturing, power, water, oil. gas, mining, retail, and many more. And use cases include things like monitoring and diagnostics, asset performance optimization, operational intelligence, and predictive maintenance.

Required Skills & Experience

  • Have analyzed, trained and deployed at least three data mining models in the past. If you have not directly deployed your own models, you should have worked with others who have put their models into production. The models should have been validated as robust over at least an initial time period.  Past algorithm deployment experience using R, SAS, MATLAB, Spark MLlib or other data mining libraries is also valid, as long as you can deploy in Python now.
  • Four or more years of full-time industry work experience, developing data mining models which were deployed and used.
  • Programming experience in Python is core using data mining related libraries like Scikit-Learn. Other relevant Python mining libraries include NumPy, SciPy and Pandas.
  • Data mining model or algorithm experience in at least 2 from the following list.  More experience on this list is a bonus.
    • Predictive or supervised algorithms may include:  regression, neural nets (backpropagation, radial basis functions or architectures from the deep learning list below), decision trees (CART, C50, Cubist, Random Forests, XGBoost), Support Vector Machines (SVM), time series or ARIMA.
    • Clustering or unsupervised algorithms may include:  K-means, DBSCAN, Gaussian Mixture Models (GMM). Other outlier or anomaly detection or non-stationary data drift detection experience is useful.
    • The past algorithm experience is valid on a wide variety of vertical applications (internet advertising, fraud detection, predicting X).  Data science project experience over different verticals is generally transferable.

Desired Skills & Experience

  • Experience in deploying (or other substantial experience) in more than 2 of the data mining algorithms in the list above.
  • Training or experience in Deep Learning, such as Keras, TensorFlow, in architectures such as convolutional neural networks (CNN), U-Net, General Adversarial Networks (GAN), Reinforcement Learning, Recurrent Nets or Long Short Term Memory (LSTM) neural network architectures. Experience in transfer learning, model shrinking or deep compression is helpful as well.
    • NOTE: if you don’t have DL experience, they will provide initial training on deep learning, to help prepare you for the mix of projects we have in our pipeline.
  • Vertical experience in Internet of Things (IoT) applications
    • Smart Cities (elevators, power, video monitoring)
    • Manufacturing (predictive maintenance on cells, or scrap prediction / classification on items produced)
    • Oil and Gas
    • Mobile phone
    • Transportation or automotive
    • Motors
    • Wind Turbines
    • Other IoT
    • Mechanical engineering or a hard sciences background helps in the development of first principle models.
  • Time series applications, Digital Signal Processing (DSP), Fast Fourier Transforms (FFT), band pass filtering, extracting features from a spectrogram and related experience is useful.
  • Experience with Complex Event Processing (CEP) or other streaming data as a data source for data mining analysis
  • Having managed past models in production over their full lifecycle until model replacement is needed. Having developed automated model refreshing on newer data.
  • Having developed frameworks for model automation as a prototype for product.
  • The model training may involve use of GPU’s. They have a Google Cloud pub-sub secure integration and are working on other cloud integrations.  Experience in different model training environments can be helpful.

What You Will Be Doing

Tech Breakdown

  • Python
  • Data Mining

Daily Responsibilities

  • Primarily, develop and deploy data mining models in a consulting role for their IoT clients to generate revenue or reduce costs. Projects are in Python Scikit-learn, to be deployed on the system with the EdgeML component.  The project duration is typically 2-3 months, but may range from 2 weeks to 6 months.
    • Some projects are in Vel, our proprietary functional streaming language that runs in a smaller footprint than Python.  Vel parallelizes naively on multicore systems, supporting DSP, a variety of numerical methods and algorithms. They provide training on Vel.
  • Secondarily, some team members may develop data science-based software applications running on our system, along with other engineers.

The Offer

  • Competitive Salary: Up to $180K/year, DOE

You will receive the following benefits:

  • Medical Insurance & Health Savings Account (HSA)
  • 401(k)
  • Paid Sick Time Leave
  • Pre-tax Commuter Benefit

 

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future.

 

Jobspring Partners, part of the Motion Recruitment network, provides IT Staffing Solutions (Contract, Contract-to-Hire, and Direct Hire) in major North American markets. Our unique expertise in today’s highest demand tech skill sets, paired with our deep networks and knowledge of our local technology markets, results in an exemplary track record with candidates and clients.

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Data Scientist - Edge Computing
  • Kyle Marquez

  • Lead Recruiter
  • Jobspring San Jose - SWD
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