Senior Data Scientist

This is a fully remote position, open to applicants in Arizona, +3 more states.

📋 Description

• Lead the collaborative development of comprehensive geospatial data science and remote sensing workflows.

• Convert project objectives and scientific inquiries into actionable plans, technical specifications, milestones, and quality benchmarks.

• Direct the selection and application of credible datasets, remote sensing products, geospatial methodologies, statistical techniques, and machine learning strategies.

• Anticipate challenges, address intricate technical problems, and balance scientific integrity with the needs of delivery and available resources.

• Design or supervise accuracy assessments, validation approaches, sampling strategies, uncertainty evaluations, and quality control processes.

• Ensure that methodologies are reproducible, thoroughly documented, and suitable for their intended purposes.

• Review code, models, data outputs, technical reports, and client submissions.

• Communicate methodological constraints, uncertainties, and result interpretations to both technical and non-technical audiences.

• Provide troubleshooting, code reviews, technical advice, and mentorship across various projects.

• Create templates, reusable code, documentation, and educational materials.

• Collaborate with project managers to assess efforts, plan technical tasks, manage dependencies, and synchronize delivery with scope and timelines.

• Contribute to research and development aimed at enhancing methods, model efficacy, processing efficiency, and data outputs.

• Assess new datasets, geospatial foundation models, cloud capabilities, and systematic methodologies.

• Offer technical expertise for proposals, scopes of work, client presentations, publications, and strategic collaborations.

• Represent CGS in conversations with clients, partners, funding organizations, government entities, and the scientific community.

⛳️ Requirements

• Ph.D. or Master’s degree along with relevant experience in data science, geography, remote sensing, hydrology, environmental science, engineering, computer science, or a similar quantitative discipline.

• Proven experience in executing the complete research lifecycle, including hypothesis formulation, experimental design, implementation, and dissemination of results.

• At least 5 years of professional experience in geospatial data science, remote sensing, environmental modeling, or a closely related area.

• Experience in designing and managing complex analytical workflows and enabling others to carry them out.

• Advanced proficiency in Python programming.

• Significant experience with raster and vector data processing, GIS applications, and large geospatial datasets.

• Strong knowledge in statistics, data science, machine learning, and remote sensing techniques.

• Practical experience in hydrology, geomorphology, terrain evaluation, or a related Earth or environmental science field.

• Familiarity with geospatial machine learning or deep learning methodologies.

• Experience with Git/GitHub, reproducible analytical practices, and collaborative code development.

• Outstanding written and verbal communication abilities.

• Background in mentoring, reviewing, or developing technical contributors.

• Capability to provide a cover letter and resume.

🏝️ Benefits

• 3x employer contribution toward retirement matching employee contributions up to 15%.

• Health insurance with no deductible.

• Dental insurance.

• Vision insurance.

• Copay assistance through an employer-funded health reimbursement account.

• Short-term disability coverage.

• Long-term disability coverage.

• Paid parental leave.

• Voluntary accident insurance.

• Health care flexible spending.

• Dependent care flexible spending.

• Paid time off for holidays, vacation, personal, sick, bereavement, and jury duty.

• Office closure from December 24 to January 1 each year.

• Flexible work schedule.

• Option for a compressed 4-day workweek.

• Tuition and staff development reimbursement.

• Pet insurance.

• Employee Assistance Program.