Data Scientist

Blue Sky Analytics

Software & Data

IT & Telecoms NGN Confidential
New
1 week ago

Job Summary

We are looking to hire a Data Scientist to join its growing team. This position will require you to think and act on the geospatial architecture and data needs (specifically geospatial data) of the company. This position is strategic and will also require you to collaborate closely with data engineers, data scientists, software developers and even colleagues from other business functions. Come save the planet with us!

  • Minimum Qualification:Degree
  • Experience Level:Entry level
  • Experience Length:2 years

Job Description/Requirements

Responsibilities:

  • You will develop data-frames and automated pipelines of data from multiple sources.
  • You are expected to know how to visualize them and use machine learning algorithms to be able to make predictions. 
  • You will curate and analyze vast amounts of geospatial datasets like satellite imagery, elevation data, meteorological datasets, open street maps, demographic data, socio-econometric data and topography to extract useful insights about the events happening on our planet.
  • You will be required to develop processes and tools to monitor and analyze data and its accuracy.
  • You will develop innovative algorithms which will be useful in tracking global environmental problems like depleting water levels, illegal tree logging, and even tracking of oil spills.


Requirements:

  • Minimum of 2 years of demonstrable industry experience working with large and noisy datasets.
  • Excellent coding skills in Python (including deep familiarity with NumPy, SciPy, pandas).
  • Significant experience with git, GitHub, SQL, AWS (S3 and EC2).
  • Worked on GIS and is familiar with geospatial libraries such as GDAL and rasterio to read/write the data, a GIS software such as QGIS for visualization and query, and basic machine learning algorithms to make predictions.
  • Demonstrable experience implementing efficient neural network models and deploying them in a production environment.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Capable of writing clear and lucid reports and demystifying data for the rest of us.
  • Be curious and care about the planet!

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