• Location: Richmond, Virginia
  • Date Posted: 25th Mar, 2020
  • Reference: W23GT4

An established, community involved tech consulting company is looking for a data scientist to help them along their journey of providing tech solutions to thriving local business in rural areas of Virginia.

About the company

Founded by business and IT professionals to provide top-notch IT services while bringing 21st century careers to rural communities in Virginia. The company is home to a talented and professional team with expertise in software application development and support, software quality assurance and testing, information management, systems engineering, and cloud consulting.

Their mission is to create sustainable IT employment opportunities for workers in rural communities.

By equipping thriving urban businesses with highly trained and qualified rural talent, the company has created a advantageous alternative to other models that offer only on site and/or offshore sourcing. Under this business model, both clients and American workers win.

Working in conjunction with several local universities, the company offers its customers the most advanced IT solutions while enabling rural IT professionals to garner the real-world experience and expertise.

The Role

You will work on-site with the local team in Richmond, Virginia to work on their data analysis, looking at industry data to identify trends, machine learning, and crunching big data.

Your responsibilities will include:

  • Lead company's RPA and machine learning initiatives

  • Analysing source and target data models

  • Perform Data Profiling, Quality Assessment, and Data Cleansing

  • Continually improve the process of data conversion, migration, and integration from legacy systems

  • Close attention to detail to ensure integrity and quality of data processes


  • Experienced with AI, "Automation Anywhere" or RPA

  • Experience in Machine Learning projects

  • Hadoop, Spark, or Splunk

  • BI and big data analysis

  • Azure/AWS Cloud experience is a bonus point but not necessary