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Applied Statistics Remote Jobs in Washington (NOW HIRING)

Cloudbolt Software Inc

Senior ML Engineer

Rockville, MD · On-site +1

$170K - $220K/yr

At CloudBolt we help organizations maximize the value of their cloud investments through greater visibility, governance, and cost optimization across complex cloud environments. Our platform empowers

ManTech

Senior Data Scientist

Arlington, VA · On-site +1

Description & Requirements Elevate your career with MANTECH International Corporation! Join a dynamic team dedicated to national security through cutting-edge technology. Since 1968, MANTECH has led

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

What Impact You'll Have GRVTY is hiring a Senior Data Scientist to support an IC program developing an enterprise-scale analytics and data management framework for geospatial intelligence products.

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

What Impact You'll Have GRVTY is hiring a Senior Data Scientist to support an IC program developing an enterprise-scale analytics and data management framework for geospatial intelligence products.

MELE Associates

Data Evaluator/Analyst

Washington, DC · On-site +1

$100/hr

MELE Associates, Inc. is seeking to add an experienced Data Evaluator/Analyst to support the Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE). EERE drives U.S.

micro1 AI

Director of Biostatistics

Alexandria, VA · Remote

$60 - $100/hr

Role Title: Biostatistician Role Type: Contractor Location: Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI benchmarking. In this role, you'll apply

micro1 AI

Biostatistician

Washington, DC · Remote

$60 - $100/hr

Role Title: Biostatistician Role Type: Contractor Location: Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI benchmarking. In this role, you'll apply

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All JobsApplied Statistics JobsApplied Statistics Remote JobsApplied Statistics Remote Jobs in Washington

Applied Statistics Remote information

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.

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

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

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

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

What cities in Washington are hiring for Applied Statistics Remote jobs?

Cities in Washington with the most Applied Statistics Remote job openings:

Applied Statistics Remote jobs near you
Infographic showing various Applied Statistics Remote job openings in Washington as of August 2026, with employment types broken down into 9% Internship, 59% Full Time, and 32% Contract. Highlights an 100% Remote job distribution.

Senior ML Engineer

Rockville, MD • On-site, Remote

Cloudbolt Software Inc
Software Development • 11 - 50 employees
Learn more about Cloudbolt Software Incexternal

$170K - $220K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago

Job description

At CloudBolt we help organizations maximize the value of their cloud investments through greater visibility, governance, and cost optimization across complex cloud environments. Our platform empowers teams to make smarter cloud decisions by turning insights into action, helping businesses improve efficiency, control spending, and accelerate innovation.
As a remote-first global SaaS company, CloudBolt is committed to fostering a collaborative, inclusive, and high-performing culture where employees can do their best work and make a meaningful impact.
Learn more at www.cloudbolt.io .
As a Senior ML Engineer, you'll be building and owning the recommendation engine at the heart of our Kubernetes resource optimization product, StormForge, cutting our customers' cloud spend without putting a workload at risk. This is a critical hands-on position at the intersection of applied machine learning and production engineering, where the hardest problems are as much about data quality, guardrails, and knowing when not to recommend as they are about forecasting itself. You'll need to bring rigor and curiosity in equal measure, designing time-series models and the fallback strategies around them, proving their behavior through repeatable regression testing, and iteratively raising the ceiling on accuracy and safety as we discover and learn more about the workloads our customers run.
Responsibilities
  • Own the recommendation engine end to end: model selection, algorithm design, preprocessing, and the guardrails that keep recommendations safe to apply to live production workloads.
  • Design, evaluate, and productionize time-series forecasting and statistical models (e.g., Prophet, percentile-based estimation) that right-size Kubernetes workloads across CPU, memory, GPU, and JVM heap.
  • Build and maintain the data-quality layer: detecting and filtering anomalies, load-test windows, startup spikes, and autoscaling artifacts from production telemetry before it reaches a model.
  • Define and continuously improve how we measure recommendation quality: regression testing against golden datasets, behavioral validation, and accuracy/safety metrics in production.
  • Investigate and resolve recommendation quality issues reported from customer environments, tracing them through data, preprocessing, and model behavior.
  • Serve as the team's machine learning authority: guide technical direction on ML questions, make model-vs-heuristic tradeoff calls, and clearly communicate them to platform engineers, product, and leadership.
  • Write production-grade Python for models and pipelines alike and share ownership of the surrounding service (message consumption, metrics ingestion, caching) with the rest of the team.
  • Prototype and validate new optimization capabilities (new resource types, new algorithms, new workload classes) from research through gradual, feature-flagged rollout.
  • Stay current on time-series forecasting and resource optimization techniques, and pragmatically evaluate which are worth adopting.

Requirements
Must have strong experience...?
  • Master's degree or higher in a quantitative field (Computer Science, Machine Learning, Statistics, Applied Mathematics).
  • 5+ years of software engineering experience, with at least 3 years building and operating machine learning or statistical systems in production.
  • Expert-level Python: you write typed, tested, production-grade code, and you're fluent in numpy or similar array-based numerical computing.
  • Hands-on experience with time-series analysis and forecasting: seasonality, trend decomposition, anomaly detection, and classical statistical methods (percentiles, distributions, smoothing), not just deep learning.
  • Experience testing ML systems rigorously: regression testing against known-good baselines, behavioral validation, and reasoning about numerical reproducibility.
  • Working knowledge of Kubernetes: resource requests and limits, autoscaling behavior, and what happens to a workload when it's under-provisioned (OOM kills, CPU throttling).
  • Comfort owning a production service, not just a model: queues, caches, retries, observability, and debugging issues in customer environments from logs and metrics.
  • Clear written and verbal communication: as an ML engineer on the team, so you must be able to explain model behavior and tradeoffs to platform engineers, product managers, and customers.

Experience in the following is beneficial
  • Experience with Prophet or similar forecasting libraries.
  • Prometheus/PromQL and experience working with metrics at scale.
  • Cloud cost optimization, capacity planning, or infrastructure efficiency background
  • AWS (S3, Managed Prometheus).
  • Experience being the ML domain expert on a team of generalists.

We Offer
Our US benefits package includes:
  • Medical/Dental/Vision coverage
  • 401k with Company Match
  • Health & Dependent Care FSA
  • Unlimited PTO
  • 11 Company Holidays
  • Volunteer/Community Engagement Day
  • Tuition Reimbursement
  • Paid Parental Leave
  • Equity Grants
  • Home internet Reimbursement

Base Salary Range: $170,000 - $220,000 USD Annually, actual compensation will be determined based on job-related factors, including but not limited to relevant experience, skills, geographic location, internal equity, and business needs.
About CloudBolt
CloudBolt is an Equal Opportunity Employer committed to building a diverse and inclusive workplace. We celebrate diversity and do not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, national origin, age, disability, protected veteran status, or any other characteristic protected by applicable law.
If you require a reasonable accommodation during the application or interview process, please contact careers@cloudbolt.io
Salary Description
$170,000 - $220,000

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