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Applied Statistics Remote Jobs in Washington, DC

The core of the work is applying machine learning, statistical analysis, and data mining techniques ... Experience with geospatial data, imagery products, or remote sensing datasets - familiarity with ...

... applied AI/ML systems and pipelines. * Bachelor's degree in CS/EE/math/statistics or a related ... Experience working with remote sensing imagery including geometry, radiometric normalization ...

The core of the work is applying machine learning, statistical analysis, and data mining techniques ... Experience with geospatial data, imagery products, or remote sensing datasets -- familiarity with ...

Biostatistician

Washington, DC ยท Remote

$60 - $100/hr

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... MS or PhD in biostatistics, statistics, or epidemiology. * 4+ years of experience in pharmaceutical ...

Data Evaluator/Analyst

Washington, DC ยท On-site +1

$100/hr

Apply econometrics and statistical modeling, including regression analysis, panel data methods, and ... Minimum 5-7 years supporting federal program evaluation or applied policy research, with increasing ...

Showing results 21-40

Applied Statistics Remote information

See Washington, DC salary details

$45.9K

$94.7K

$132.5K

How much do applied statistics remote jobs pay per year?

As of Aug 17, 2026, the average yearly pay for applied statistics remote in Washington, DC is $94,749.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,600.00 and $131,400.00 per year, depending on experience, location, and employer.

What is an applied statistics remote job?

An Applied Statistics Remote job involves using statistical methods and data analysis techniques to solve real-world problems, all while working from a remote location. Professionals in this field collect, analyze, and interpret data to provide insights for decision-making across various industries such as healthcare, finance, and technology. Remote applied statisticians often collaborate virtually with teams, utilize statistical software, and communicate findings through reports or presentations. This role requires strong analytical skills, proficiency in statistical tools, and the ability to work independently.

What are the key skills and qualifications needed to thrive as an applied statistics professional in a remote role?

To thrive as an Applied Statistics professional working remotely, you need a solid background in statistical theory, data analysis, and a degree in statistics, mathematics, or a related field. Proficiency with statistical software such as R, Python, SAS, or SPSS, and familiarity with data visualization tools are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills are essential for interpreting data and collaborating virtually. These skills ensure accurate analyses, clear insights, and successful teamwork, which are crucial for delivering impactful statistical solutions in a remote environment.

How does working remotely in an applied statistics role influence collaboration and project management with cross-functional teams?

In a remote applied statistics position, collaboration often relies on digital tools such as video conferencing, shared code repositories, and project management platforms. Statisticians frequently work with data scientists, engineers, and business stakeholders, making clear communication and documentation essential for successful project outcomes. Regular virtual meetings and asynchronous updates help align team objectives and ensure data-driven insights are integrated effectively. While remote work offers flexibility, it also requires proactive engagement to stay connected and maintain productivity within a distributed team environment.

What is the difference between Applied Statistics Remote vs Data Analyst?

AspectApplied Statistics RemoteData Analyst
Required CredentialsBachelor's or Master's in Statistics, Mathematics, or related fieldBachelor's in Statistics, Data Science, or related field
Work EnvironmentRemote, often project-based or contract rolesRemote or on-site, typically in corporate or tech settings
Industry UsageResearch, academia, consulting, tech companiesBusiness, finance, marketing, tech companies
Common Search/ComparisonApplied Statistics RemoteData Analyst

Applied Statistics Remote and Data Analyst roles share similar educational backgrounds and often work in remote environments. However, Applied Statistics Remote roles tend to focus more on statistical modeling and research, while Data Analysts often handle data visualization and reporting for business insights. Both roles are in high demand across various industries, with Applied Statistics Remote positions leaning more toward research and academic projects.

Is applied statistics a good career?

Applied statistics is a strong career choice for those interested in data analysis, modeling, and decision-making, often requiring skills in programming languages like R or Python. It offers opportunities across various industries such as healthcare, finance, and technology, with competitive salaries and demand for professionals with statistical expertise. Continuous learning and certification can enhance job prospects in this field.

Where can I work with a degree in applied statistics?

With a degree in applied statistics, you can work in various industries such as healthcare, finance, marketing, and technology, often as a data analyst, statistician, or data scientist. These roles typically require skills in statistical software, programming languages like R or Python, and data visualization tools. Many positions are available in both remote and on-site environments across multiple sectors.

What are popular job titles related to Applied Statistics Remote jobs in Washington, DC?

For Applied Statistics Remote jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Applied Statistics Remote jobs in Washington, DC look for?

The top searched job categories for Applied Statistics Remote jobs in Washington, DC are:

Infographic showing various Applied Statistics Remote job openings in Washington, DC as of August 2026, with employment types broken down into 10% Internship, 60% Full Time, and 30% Contract. Highlights an 100% Remote job distribution, with an average salary of $94,749 per year, or $45.6 per hour.

Data Scientist II

LINCOLN INSTITUTE OF LAND POLICY

Washington, DC โ€ข On-site, Remote

$95K/mo

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago


Job description

Job DetailsLevel: ExperiencedJob Location: Washington DC - Washington, DC 20005Position Type: Fixed TermEducation Level: Graduate DegreeSalary Range: $76,000.00 - $95,000.00 SalaryTravel Percentage: Up to 10%Job Category: ProgramWho We Are The Center for Geospatial Solutions (CGS) is a self-sustaining nonprofit enterprise. Founded to help bridge the gap between policy and practice, our mission is to enable people and the planet to meet the pace of change by expanding access to new technologies that power more sustainable and equitable outcomes. We are a fully remote team of award-winning professionals with decades of applied expertise and end-to-end GIS capabilities. By embracing whole-system thinking and state-of-the-art technology, we enable partners across public, private, and nonprofit sectors to tackle complex, real-world challengesโ€”like housing affordability, ecosystem conservation, water management, and sustainable infrastructureโ€”with greater clarity. Our work liberates and connects key information, creates nuanced pictures of complex situations, and makes land, water, and social data easier to use, understand, and act on. We use tools like satellite data and artificial intelligence to deliver insights for impact. At CGS, we believe that technology can be a tool for positive change. We are dedicated to building a diverse team that represents the communities and systems we live and work in. If youโ€™re excited about this role but donโ€™t meet every listed qualification, we encourage you to apply. We value potential, curiosity, and lived experiences, and know a more inclusive team makes us a stronger organization. About the Lincoln Institute CGS was established in 2020 at the Lincoln Institute of Land Policy, which seeks to improve quality of life through the effective use, taxation, and stewardship of land. A nonprofit private operating foundation whose origins date to 1946, the Lincoln Institute researches and recommends creative approaches to land as a solution to economic, social, and environmental challenges. Through education, training, publications, and events, the Lincoln Institute integrates theory and practice to inform public policy decisions worldwide and has office locations in Cambridge, Massachusetts; Washington, DC; Phoenix, Arizona; and Beijing, China. Position Overview The Center for Geospatial Solutions (CGS) is seeking a Data Scientist II to implement geospatial data science, remote sensing, and environmental modeling workflows that support real-world choices about land, water, conservation, infrastructure, and related challenges. Reporting to the Associate Director of Data Science, the Data Scientist will acquire and evaluate data, run and improve analytical workflows, conduct accuracy assessments, document results, and help automate repeatable processing steps. The role will exercise sound judgment about data quality, appropriate methods, and issues that should be elevated to senior technical staff. This position is well suited to an applied data scientist who is comfortable moving between geospatial analysis, Python-based processing, remote sensing, statistics, and collaborative project delivery. The successful candidate will be eager to deepen their expertise while producing reliable, reproducible work that can scale across projects and geographies. What You Will Do Geospatial Analysis and Workflow Implementation \tImplement established geospatial data science and remote sensing workflows from data acquisition through processing, analysis, model execution, validation, and delivery. \tAcquire, organize, clean, and evaluate raster, vector, tabular, terrain, and Earth observation datasets from public, partner, and client sources. \tUse Python, GIS software, and open-source tools to process large geospatial datasets and generate repeatable analytical outputs. \tRun geospatial machine learning or deep learning workflows, evaluate model outputs, and identify important performance issues or data limitations. \tExercise judgment about the best available data, important caveats, and technical issues that should be elevated to senior technical staff. Validation, Documentation, and Quality \tConduct spatial statistics, accuracy assessments, quality-control checks, and validation using established methods. \tPrepare clear documentation of data sources, processing steps, code, assumptions, limitations, and results. \tReview outputs for completeness, consistency, and technical quality before they are shared with partners or clients. \tContribute to reproducible project structures, data dictionaries, metadata, and technical handoff materials. Automation and Process Improvement \tIdentify repetitive or error-prone steps that can be automated, standardized, or made more efficient. \tDevelop and maintain scripts, functions, notebooks, and reusable components that improve delivery speed and consistency. \tWork with senior data scientists, AI engineers, and cloud engineers to move useful prototypes toward scalable workflows. \tTest new datasets and methods and share practical findings with the broader technical team. Collaboration and Delivery \tWork closely with senior technical staff, AI engineers, GIS professionals, project managers, and subject-matter experts. \tCommunicate progress, technical considerations, results, and risks clearly in team meetings, written updates, and presentations. \tContribute to client deliverables, proposals, technical memos, presentations, and demonstrations. \tParticipate in peer review and contribute to an inclusive team culture focused on learning, quality, and impact. What You Will Need: \tMasterโ€™s degree or equivalent experience in data science, geography, remote sensing, environmental science, engineering, computer science, or a related quantitative field. \t2-5 years of professional experience applying geospatial analysis, data science, remote sensing, or environmental modeling to solve real world problems and address stakeholder needs \tProficiency in Python for data engineering and data science workflows, including experience with common geospatial and scientific libraries. \tExperience with raster and vector data, GIS software such as Esri or open-source equivalents, and large geospatial datasets. \tStrong foundation in statistics, data science, machine learning, and remote sensing. \tExperience acquiring, cleaning, evaluating, and documenting data from multiple sources. \tExperience independently designing and implementing GeoAI models and other analytical approaches, addressing open-ended problems with incomplete or evolving requirements. \tExperience with Git/GitHub or comparable version-control workflows. \tStrong attention to detail and commitment to reproducible, well-documented work. \tClear written and verbal communication skills and the ability to collaborate effectively in a fully remote environment. \tCollaborative and able to work successfully in interdisciplinary teams with colleagues from various topical backgrounds and different skill levels and communication levels \tExceptional critical thinking skills with the ability to deconstruct complex problems, prioritize issues, and implement sensible solutions \tExperience translating client needs into clear milestones, scopes of work, and risk assessments \tStrong ability to communicate technical and computational concepts clearly to non-technical audiences, including domain experts, stakeholders, and partners \tSelf-motivated and goal-oriented with the ability to take an innovative, strategic, and evidence-based approaches to research and empathetic collaboration \tWillingness and ability to learn new frameworks, data structures, and infrastructure \tU.S. Citizen, or legally authorized to work in the United States with no need for future sponsorship Helpful Experience (Nice to Have): \tExperience with hydrology, geomorphology, terrain analysis, wetlands, ecology, or other environmental domains. \tExperience with cloud-based processing using AWS, Azure, Google Cloud, Google Earth Engine, or similar platforms. \tExperience with geospatial foundation models, embeddings, or large-scale Earth observation datasets. \tExperience contributing to academic or applied research, including study design, analysis, and communication of findings. \tExperience with field data, wetland delineations, survey data, or validation datasets. \tExperience supporting government, nonprofit, or consulting projects and working within defined scopes and deadlines. Application Process Please submit a cover letter and resume. The cover letter should succinctly describe your interest in joining the CGS team; why you are qualified; and what relevant expertise and experience you offer. Applications will be considered on a rolling basis until the position is filled.   Compensation Overview The salary market range for this role is posted above and dependent on level of education and years of experience. We value internal and external equity and encourage those who may be missing qualifications to submit their materials still.   Our Benefits Our Benefits Benefits highlights include but are not limited to (a) 3x employer contribution towards retirement matching your employee contribution up to 15%, (b) health insurance with no deductible (c) dental insurance, (d) vision insurance, (e) copay assistance through an employer-funded health reimbursement account, (f) short-term disability coverage, (g) long term disability coverage, (h) paid parental leave, (i) voluntary insurances such as accident insurance, (j) health care flexible spending, (k) dependent care flexible spending, (l) paid time off for holidays, vacation, personal, sick, bereavement, and jury duty, (m) office closure between December 24 Jan 1 each calendar year, (n) flexible schedule and option for a compressed 4 day workweek, (o) tuition and staff development reimbursement, (p) pet insurance, and (q) Employee Assistance Program.   Our Values Cooperation and Teamwork, Forthright Feedback, Initiative, Acceptance of Responsibility, Multicultural Sensitivity   Equal Opportunity Employer The Lincoln Institute of Land Policy is dedicated to creating an inclusive work environment by hiring, training, promoting, and carrying out personnel procedures with respect to compensation, benefits, transfers, layoffs, or terminations, on the basis of individual merit, experience, and ability without regard to race (including traits historically associated with race such as hair texture, length of hair, protective hairstyles or cultural or religious headdresses), color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), ancestry, citizenship status, gender identity or expression, genetic information, marital or domestic/civil partnership status, physical or mental disability, sexual orientation, veteran status, military service, serious medical condition, expunged juvenile record, personal appearance, family responsibilities, matriculation, political affiliation, status as a victim, credit information, homelessness status, reproductive health decision making, or any other characteristic protected by law or otherwise.    Pay Transparency Nondiscrimination Provision Lincoln Institute of Land Policy will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractorโ€™s legal duty to furnish information.   Non-Smoking Organization Lincoln Institute of Land Policy is a Non-Smoking organization. Smoking and the use of tobacco products are prohibited at all times and on all property owned, leased, or under the control of Lincoln Institute of Land Policy at all times, including, but not limited to indoor and outdoor grounds, walkways and sidewalks, parking lots, company vehicles, and private vehicles parked on Lincoln Institute of Land Policy property.   MA Polygraph Statement It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. QualificationsWhat You Will Need \tMasterโ€™s degree or equivalent experience in data science, geography, remote sensing, environmental science, engineering, computer science, or a related quantitative field. \t2-5 years of professional experience applying geospatial analysis, data science, remote sensing, or environmental modeling to solve real world problems and address stakeholder needs \tProficiency in Python for data engineering and data science workflows, including experience with common geospatial and scientific libraries. \tExperience with raster and vector data, GIS software such as Esri or open-source equivalents, and large geospatial datasets. \tStrong foundation in statistics, data science, machine learning, and remote sensing. \tExperience acquiring, cleaning, evaluating, and documenting data from multiple sources. \tExperience independently designing and implementing GeoAI models and other analytical approaches, addressing open-ended problems with incomplete or evolving requirements. \tExperience with Git/GitHub or comparable version-control workflows. \tStrong attention to detail and commitment to reproducible, well-documented work. \tClear written and verbal communication skills and the ability to collaborate effectively in a fully remote environment. \tCollaborative and able to work successfully in interdisciplinary teams with colleagues from various topical backgrounds and different skill levels and communication levels \tExceptional critical thinking skills with the ability to deconstruct complex problems, prioritize issues, and implement sensible solutions \tExperience translating client needs into clear milestones, scopes of work, and risk assessments \tStrong ability to communicate technical and computational concepts clearly to non-technical audiences, including domain experts, stakeholders, and partners \tSelf-motivated and goal-oriented with the ability to take an innovative, strategic, and evidence-based approaches to research and empathetic collaboration \tWillingness and ability to learn new frameworks, data structures, and infrastructure \tU.S. Citizen, or legall