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Data Scientist R Remote Jobs in Baltimore, MD (NOW HIRING)

Data Engineer (Remote)

Baltimore, MD · Remote

$117K - $140K/yr

Bachelor's degree in computer science, engineering, statistics, or related field. * 4+ years of experience in a data engineering, data pipeline, or ETL/ELT development role. * Strong proficiency in ...

NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D. Whenever possible ... While many positions offer remote or hybrid work options, these arrangements are subject to change ...

NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D. Whenever possible ... While many positions offer remote or hybrid work options, these arrangements are subject to change ...

Data Architect (2 openings) - IRS Clearance 6-month contract-to-hire Remote, Greenbelt, MD Bachelor ... technology, life sciences, and government sectors. We partner with large private and public ...

Current undergraduate or graduate student studying public health, data science, social sciences, or ... Ability to work independently in a remote environment and stay on top of assigned tasks. Preferred ...

Data Engineer II

Baltimore, MD · Remote

$113K - $136K/yr

Remote first work environment * Collaborative, cross-functional technology team * Fast-paced ... Bachelor's degree in Computer Science, Business Administration, Information Systems, or a related ...

Remote Job Duration: Fulltime Client: Federal Criteria- Need ship because of federal regulations ... Ability to obtain Public Trust Clearance * 5+ years of experience in AI/ML, Data Science, Data ...

Showing results 41-60

Data Scientist R Remote information

See Baltimore, MD salary details

$37.3K

$122K

$195.3K

How much do data scientist r remote jobs pay per year?

As of Aug 10, 2026, the average yearly pay for data scientist r remote in Baltimore, MD is $121,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $135,100.00 per year, depending on experience, location, and employer.

What is a data scientist R remote?

Data Scientist R Remote jobs are positions where professionals use the R programming language to analyze and interpret complex data, develop statistical models, and generate actionable insights, all while working outside of a traditional office setting. These roles often involve collaborating with teams virtually, cleaning and preparing data, and building predictive models using R and related tools. Remote data scientists leverage cloud-based platforms and communication tools to work effectively from any location. The role typically requires strong analytical skills, proficiency in R, and experience with data visualization and machine learning techniques.

How does a remote data scientist specializing in R typically collaborate with cross-functional teams?

As a remote Data Scientist with expertise in R, collaboration with cross-functional teams—such as product managers, engineers, and business analysts—is commonly facilitated through virtual meetings, shared documentation, and version control systems like Git. You'll often participate in sprint planning, present data-driven insights, and contribute to collaborative code reviews. Effective communication and proactive sharing of progress or challenges are key to ensuring alignment, especially when working across time zones. Utilizing tools like Slack, Jira, and cloud-based notebooks further streamlines teamwork and maintains project momentum.

What are the key skills and qualifications needed to thrive as a data scientist R remote?

To thrive as a Data Scientist (R, Remote), you need strong analytical skills, statistical knowledge, and a background in mathematics or computer science, often supported by a relevant degree. Proficiency in R programming, data visualization tools, and familiarity with machine learning libraries are typically required, and certifications like the Microsoft Certified: Azure Data Scientist Associate can be advantageous. Excellent problem-solving abilities, effective communication, and self-motivation are critical soft skills for collaborating remotely and translating data insights into actionable business decisions. These skills enable you to derive meaningful insights from complex data sets, drive data-driven strategies, and work efficiently in a remote team environment.

What is the difference between Data Scientist R Remote vs Data Analyst R Remote?

AspectData Scientist R RemoteData Analyst R Remote
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; proficiency in RBachelor's in Statistics, Mathematics, or related field; proficiency in R
Work EnvironmentRemote, collaborative teams, project-basedRemote, reporting to managers, data reporting tasks
Employer & Industry UsageTech, finance, healthcare, consultingRetail, marketing, finance, healthcare
Common Search & ComparisonYesYes

Data Scientist R Remote and Data Analyst R Remote roles share similar skills in R programming and remote work environments. However, Data Scientists typically handle complex modeling, machine learning, and predictive analytics, requiring advanced statistical knowledge. Data Analysts focus on data reporting, visualization, and descriptive analysis. Both roles are vital across industries, but Data Scientists often require higher-level credentials and experience.

Infographic showing various Data Scientist R Remote job openings in Baltimore, MD as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% Remote job distribution, with an average salary of $121,958 per year, or $58.6 per hour.

Data Engineer - ML/AI Data Platform (Remote)

FEI Systems

Columbia, MD • On-site, Remote

$111K - $133K/yr

Full-time

Re-posted 2 days ago


Job description

At FEI Systems, we create innovative technology solutions to improve the delivery of health and human services because we know when cumbersome administrative processes stand in the way, those who need it most are often left without access to proper care and support. From comprehensive case management software to disaster recovery services and content management information systems used in delivering foreign aid, our solutions are improving the lives of millions of people. We're looking for a data engineer who shares our commitment to leveraging technology to make a real impact in the world - a professional who knows, beyond all else, that the quality of our products and services is only as good as the company we keep.
All candidates will be required to complete at least one in-person interview as part of our hiring process.
Role Overview
We are seeking a Data Engineer to support Machine Learning and AI initiatives. Working closely with the Solution Architect, Data Architect, DevOps, and Application Engineering teams, this role is responsible for ensuring that data within our cloud-based platform is high quality, well-governed, feature-ready, and production-grade to support model training, deployment, and ongoing operations.
The ideal candidate has 5+ years of cloud data engineering experience with strong proficiency in Snowflake, Python, and SQL, and solid familiarity with AWS-native data services.
Candidates are not expected to arrive with expertise across every area listed. We are looking for demonstrated strength in the core data engineering and Snowflake skills, combined with the initiative and aptitude to grow into the broader scope of the role.
Day-One Priorities & Scope
Immediate focus is Snowflake-based data engineering, pipeline development, and data quality. Feature engineering, model training support, and MLOps contributions are growth areas that will ramp over time as you become embedded with the team.
Key Responsibilities
Data Pipeline Engineering
  • Design, build, and maintain scalable data pipelines supporting ML/AI workloads.
  • Engineer pipeline patterns including full loads, incremental loads, change-based loads, and slowly changing dimensions.
  • Ensure pipelines are reliable, performant, secure, and maintainable, troubleshoot and monitor pipelines within an AWS ecosystem.

Snowflake & Cloud Data Engineering
  • Perform data transformations in Snowflake using SQL and native Snowflake features.
  • Design and optimize schemas, tables, views, and materialized views for ML/AI consumption.
  • Support AWS-native data lake patterns using S3, Glue, Athena, Apache Iceberg, and S3 Tables.

Feature Engineering & Data Preparation
  • Perform data cleansing, normalization, and enrichment to support ML model development.
  • Design and implement feature engineering pipelines including aggregation and transformation.
  • Ensure consistency, reuse, and versioning of features across models and use cases.
  • Support feature store patterns to enable feature discoverability and reuse.
  • Collaborate with ML engineers and data scientists to operationalize features into training pipelines.

Model Training & MLOps Support
  • Support model training workflows, including dataset preparation and scheduled refreshes.
  • Ensure training datasets and features are reproducible, traceable, and auditable.
  • Integrate data pipelines into CI/CD workflows; support version control, testing, and deployment of data assets.
  • Monitor pipeline health, data freshness, and downstream impact on ML/AI systems.

Required Skills & Experience
5+ years of hands-on data engineering experience in a cloud environment.
Core Technologies
  • Python - strong proficiency for data processing and pipeline development.
  • SQL - advanced skills with hands-on Snowflake transformation experience.
  • Snowflake - ELT pipeline design, schema optimization, performance tuning, cost management.
  • PostgreSQL - experience with querying, data modeling, and analytics; familiarity with SQL Server to PostgreSQL migration a plus.
  • AWS - S3, Glue, Athena, Snowflake integration, and managed relational databases (e.g., Aurora, RDS).
  • Apache Iceberg / S3 Tables - familiarity with open table format ecosystems.
  • Streaming ingestion tools (e.g., Kinesis, Kafka, or equivalent).
  • Workflow orchestration tools (e.g., Airflow, Step Functions, or equivalent).

Pipeline & Data Engineering
  • Experience with full loads, incremental loads, append-only pipelines, change-based processing, and SCDs.
  • Data validation, reconciliation, error handling, and restart/recovery patterns.
  • Data modeling for analytics, ML/AI, and downstream application use cases.
  • Ability to evaluate pipeline design trade-offs across performance, cost, reliability, and maintainability.

DevOps & Engineering Practices
  • Structured SDLC experience with CI/CD pipelines for data and ML workflows.
  • API-based and event-driven data integration patterns.
  • Distributed data processing environments.

ML/AI Data Foundations
  • Understanding of data requirements for ML/AI workloads.
  • Experience preparing training datasets and features from enterprise data lakes.
  • Familiarity with reproducibility, dataset versioning, and data lineage concepts.
  • Familiarity with GenAI concepts relevant to data engineering, such as embedding pipelines, vector databases, retrieval-augmented generation (RAG) data flows, or prompt-driven data processing - including awareness of data security and privacy considerations when working with LLMs.

Education
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field. Equivalent professional experience will be considered.
Location: Remote
Status: Full time position with full company benefits.
NOTICE: EO/AA/VEVRAA/Disabled Employer - Federal Contractor. FEI Systems participates in E-Verify, a federal program that enables employers to verify the identity and employment eligibility of all persons hired to work in the United States by providing the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee's Form I-9 to confirm work authorization. For more information on E-Verify, please contact DHS at (888) 464-4218.
Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, marital status, political affiliation, disability, or genetic information, except where it relates to a bona fide occupational qualification or requirement. FEI Systems creates an Affirmative Action Plan on an annual basis. Pursuant to federal law, the portions of FEI Systems' Affirmative Action Program that relate to Section 503 (Persons with Disabilities) and/or Section 4212 (Protected Veterans), are available for inspection upon request by applicants and employees during FEI Systems' normal business hours.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.