Applied Python Analyst - Moscow, United States - Geosearch

Description

Job Description

Job Description

GeoSearch is actively looking for an Applied Python Analyst.

The main responsibilities of this position are designing and testing automated data pipelines, statistical modeling, and method/product development and documentation within the Companys Lidar services.

Developing, troubleshooting, and validating custom-built, innovative programs to interpret and analyze Lidar data, as well as graphical and statistical presentation of these data/methods to the team is the day-to-day.

Lidar data analysis, datamining, statistical testing, and an understanding of machine learning, deep learning, and CNNs are at the foundation of this positions skills.

Communication and innovation are essential. This position will additionally provide introductory training to other Company staff regarding workflow processes, Python programming, applied statistics, and/or

datamining/interpretation.

We are ideally looking for a candidate to work on-site in Moscow, ID. Relocation assistance can be provided for the right candidate.


Duties and Responsibilities:
Code, test, and apply statistical models for geospatial and data-mining applications with Lidar data on natural landscapes.

Develop innovative methods for answering client requests with Lidar data and expand the teams applications of these data in natural resource management and stewardship.

Analyze and resolve technical, mathematical, and statistical problems.
Write functional and detailed design documentation, program specifications, test plans, and other system documentation.
Independently recognize and resolve methodological and/or conceptual errors within our workflows.
Maintain integrity of program logic and style and establish required checks and balances for operational controls.
Participate as a team member to plan, design, develop, test, and continually improve the quality and efficiency of products.

Continue to expand the technical services network through targeted participation in promotional activities, proposal development, budgeting and project management related to remote sensing and GIS, as requested.

Ability to spend up to two (2) weeks in the field at a time with minimal supervision collecting geospatial field data anywhere in continental USA.

Qualifications:

An MS or PhD degree in geology, physics, mathematics, computer science, or other highly technical field with a connection to research on natural environments; and a minimum of two (2) years experience in quantitative data analysis, software development, and/or applied statistical modeling.

Highly skilled with Python, and/or R.
Ability to design, develop, test, document, apply, and explain

statistical/mathematical

methods to extract actionable information from large, complex data sets that include 3D point clouds.
Ability to create and interpret complex statistical models and their predictions.
Demonstrated background in statistical accuracy-testing and modeling.

Additional Desirable

Qualifications:
Demonstrated expertise in neural networks, computer vision, data mining, machine learning, and/or deep learning. Experience with machine learning methods and tools including scikit-learn and Keras among others.
Experience working with remote sensing data (Imagery, Radar, etc.) and geospatial data structures in Python.
Experience with LiDAR data manipulation, acquisition technology and/or software applications in Python.
Publication experience as a lead author in a scientific peer-reviewed journal.
Experience with relational databases and SQL or PostgreSQL.
Creative and versatile data visualization skills.


Benefits:

Competitive wage:

DOE
Paid holidays, vacation, and sick leave
Healthcare, including Medical, Dental, Vision, and Prescription Benefits
Flexible spending account (FSA) for health care costs
Life insurance, short-term and long-term disability plan
401k retirement plan with company contribution (after one year of service)
On-the-job training, skills development, and career advancement opportunities
Professional development support
Employee recognition programs
A supportive and engaging work culture promoting healthy living

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