Data Scientist (iot)

Job Description

Roles and Responsibilities

Execute data mining projects, training and deploying models over a typical duration of 2 -12 months.

He/She should be able to innovate, analyze the customer requirement, develop a solution in the time box of the project plan, execute and deploy the solution.

Integrate the data mining projects embedded data mining applications in the FogHorn platform (on Docker or Android).

Core Qualifications

Have analyzed, trained and deployed at least three data mining models in the past. If the candidate did not directly deploy their own models, they will 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.

Three years of 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 algorithm experience in at least 3 algorithms across: prediction (statistical regression, neural nets, deep learning, decision trees, SVM, ensembles), clustering (k-means, DBSCAN or other) or Bayesian networks

Good to have:

Have managed past models in production over their full life cycle until model replacement is needed. Have developed automated model refreshing on newer data. Have developed frameworks for model automation as a prototype for product.

Training or experience in Deep Learning, such as TensorFlow, Keras, convolutional neural networks (CNN) or Long Short Term Memory (LSTM) neural network architectures. If you don’t have deep learning experience, we will train you on the job.

Shrinking deep learning models, optimizing to speed up execution time of scoring or inference.

OpenCV or other image processing tools or libraries

Cloud computing: Google Cloud, Amazon AWS or Microsoft Azure. We have integration with Google Cloud and are working on other integrations.

Decision trees like XGBoost or Random Forests is helpful.