2

Part Time Geology Data Science Jobs in Spokane, WA

Part Time Phlebotomist

Liberty Lake, WA · On-site

$17.75 - $26.42/hr

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Together, we're improving health and improving lives. Part Time Phlebotomist - PAML Labcorp is a ...

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Together, we're improving health and improving lives. Part Time Phlebotomist - PAML Labcorp is a ...

Part Time Phlebotomist

Liberty Lake, WA · On-site

$17.75 - $26.42/hr

Through our unparalleled science, data, technology and laboratory network, we advance diagnostics ... Together, we're improving health and improving lives. Part Time Phlebotomist - PAML Labcorp is a ...

Overview Registered Nurse - Full Time - Post Falls, Idaho Part Time and Per Diem options available ... Bachelor of Science in Nursing degree preferred. * Current state license as a Registered Nurse ...

next page

Showing results 1-20

Part Time Geology Data Science information

See Spokane, WA salary details

$36.4K

$77.9K

$125.9K

How much do part time geology data science jobs pay per year?

As of Aug 25, 2026, the average yearly pay for part time geology data science in Spokane, WA is $77,887.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,600.00 and $94,000.00 per year, depending on experience, location, and employer.

What is a part-time geology data scientist?

A part-time geology data scientist is a professional who applies data science techniques to analyze geological data, such as rock samples, seismic data, or mineral compositions, while working less than full-time hours. They use statistical analysis, machine learning, and data visualization to interpret complex geological information and support decision-making in areas like resource exploration or environmental monitoring. Part-time roles offer flexibility, making them ideal for students, professionals seeking work-life balance, or those supplementing other careers. Responsibilities may include data cleaning, creating predictive models, and collaborating with geologists and engineers. These professionals are valuable in industries like mining, oil and gas, environmental consulting, and academia.

What are the key skills and qualifications needed to thrive as a part-time geology data scientist?

To thrive as a Part Time Geology Data Scientist, you need a solid background in geology, statistical analysis, and data science, often supported by a relevant degree. Familiarity with programming languages like Python or R, GIS software, and data visualization tools is typically required. Strong problem-solving, communication, and time management skills help you interpret complex data and share insights effectively. These capabilities are crucial for extracting actionable geological insights from data while balancing part-time responsibilities.

What are the typical responsibilities and collaboration opportunities for a part-time geology data science role?

In a part-time Geology Data Science position, you can expect to work on tasks such as cleaning and analyzing geological datasets, creating visualizations, and supporting research or exploration projects with data-driven insights. You’ll often collaborate with geologists, engineers, and IT professionals to interpret findings and contribute to decision-making processes. Communication skills are important, as you'll need to explain complex data trends to colleagues who may not have a data science background. The role offers valuable experience in both geoscience and analytics, which can open doors for future full-time opportunities or specialized advancement in the field.

What is the difference between Part Time Geology Data Science vs Part Time Environmental Data Science?

AspectPart Time Geology Data SciencePart Time Environmental Data Science
Required CredentialsGeology or Earth Science degree, Data Science skillsEnvironmental Science or related degree, Data Science skills
Work EnvironmentMining sites, geological surveys, research labsEnvironmental agencies, consulting firms, research institutions
Industry UsageMining, oil & gas, geological explorationEnvironmental consulting, conservation, policy analysis
Search & Comparison IntentUnderstanding geology-focused data roles in part-time settingsExploring environmental data science opportunities part-time

Part Time Geology Data Science involves analyzing geological data within industries like mining and oil & gas, often requiring geology credentials. In contrast, Part Time Environmental Data Science focuses on environmental data for conservation and policy, typically needing environmental science backgrounds. Both roles utilize data science skills but serve different industry needs and work environments.

What are the most commonly searched types of Geology Data Science jobs in Spokane, WA?

The most popular types of Geology Data Science jobs in Spokane, WA are:

What cities near Spokane, WA are hiring for Part Time Geology Data Science jobs?

Cities near Spokane, WA with the most Part Time Geology Data Science job openings:

$49K/yr

Full-time, Part-time

Re-posted 19 days ago


Job description

The PALACE Acquire Program offers you a permanent position upon completion of your formal training plan. As a Palace Acquire Intern you will experience both personal and professional growth while dealing effectively and ethically with change, complexity, and problem solving. The program offers a 3-year formal training plan with yearly salary increases. Promotions and salary increases are based upon your successful performance and supervisory approval.Qualifications:BASIC REQUIREMENT OR INDIVIDUAL OCCUPATIONAL REQUIREMENT:
Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
You may qualify if you meet one of the following:
1. GS-7: You must have completed or will complete a 4-year course of study leading to a bachelor's from an accredited institution AND must have documented Superior Academic Achievement (SAA) at the undergraduate level in the following:
a) Grade Point Average 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum.
2. GS-9: You must have completed 2 years of progressively higher-level graduate education leading to a master's degree or equivalent graduate degree:
a) Grade Point Average - 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum. If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP, CCAF, DANTES, military credit, etc. you cannot qualify based on GPA.
KNOWLEDGE, SKILLS AND ABILITIES (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies in the following areas:
1. Professional knowledge of basic principles, concepts, and practices of data science to apply scientific methods and techniques to analyze systems, processes, and/or operational problems and procedures.
2. Knowledge of mathematics and analysis to perform minor phases of a larger assignment and prepare reports, documentation, and correspondence to communicate factual and procedural information clearly.
3. Skill in applying basic principles, concepts, and practices of the occupation sufficient to perform routine to difficult but well precedented assignments in data science analysis.
4. Ability to analyze, interpret, and apply data science rules and procedures in a variety of situations and recommend solutions to senior analysts.
5. Ability to analyze problems to identify significant factors, gather pertinent data, and recognize solutions.
6. Ability to plan and organize work and confer with co-workers effectively.
PART-TIME OR UNPAID EXPERIENCE: Credit will be given for appropriate unpaid and or part-time work. You must clearly identify the duties and responsibilities in each position held and the total number of hours per week.
VOLUNTEER WORK EXPERIENCE: Refers to paid and unpaid experience, including volunteer work done through National Service Programs (i.e., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community; student and social). Volunteer work helps build critical competencies, knowledge and skills that can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:IF USING EDUCATION TO QUALIFY: If position has a positive degree requirement or education forms the basis for qualifications, you MUST submit transcriptswith the application. Official transcripts are not required at the time of application; however, if position has a positive degree requirement, qualifying based on education alone or in combination with experience, transcripts must be verified prior to appointment. An accrediting institution recognized by the U.S. Department of Education must accredit education. Click here to check accreditation.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying.Employment Type: OTHER