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terrestris GmbH & Co. KG · 3 months ago

Data Scientist / Manager

Asheville, NC

Full-time

Onsite

Mid, Senior Level

1+ years exp

Terrestris, LLC is an innovative organization seeking a Data Scientist / Manager to support the USDA Forest Service in North Carolina. The role involves analytics, data management, and developing data-driven solutions to enhance agency performance and decision-making.

Information ServicesInformation TechnologySoftware

No H1B

Responsibilities

Consult with cross-functional teams on the design and conduct of projects or studies to evaluate and resolve complex problems

Advise on the potential of data to provide new insights into the agency's mission

Identify, collect, cleanse, and analyze structured and unstructured data used to support assigned projects or program(s)

Explore patterns, correlations, and causations from various systems and datasets to provide a synopsis of emerging trends, challenges, and recommendations for change

Apply data visualization techniques, such as dashboards, scorecards, and graphs, to create solutions that enable enhanced agency performance and decision making

Participate in the preparation and presentation of project briefings to communicate results and recommendations for operational improvements

Manage, input, extract and interpret data using Forest Service asset management software

Perform various routine administrative tasks and interface with multiple resource groups to maintain complete and accurate databases of asset portfolios in accordance with USDA directives

Qualification

Data analyticsPythonRStatistical techniquesMachine learningData visualizationUSDAFederal data governanceCross-functional collaborationProblem-solvingCommunication skills

Required

Authorization to work in the U.S. permanently without sponsorship

A Bachelor's Degree with (2) years of relevant experience OR a Master's degree and (1) year of relevant experience OR (10) years of relevant experience, in lieu of an education credential (Relevant Experience is defined as work involving data analytics; data input, retrieval and visualization; programming and automation using Python, R, or similar; and/or applying statistical techniques and machine learning.)