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Remote Data Science Jobs in Towson, MD (NOW HIRING)

Magpie Health Analytics

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 ...

Sbdinc

Senior Manager, Data Engineering

Towson, MD · Remote

Senior Manager, Data Engineering - Remote Towson, MD USA Come make the world and accelerate your ... You also have: * Bachelor's degree from an accredited institution in Computer Science, Data ...

Under Armour

Sr. Data Analytics Engineer

Baltimore, MD · On-site +1

$125K - $165K/yr

As a Senior Data Engineer, you will design and implement data analytics pipelines, develop high ... Location: Remote (East Coast strongly preferred to optimize collaboration with HQ and cross ...

micro1 AI

Domain Expert - (STEM PhD)

Baltimore, MD · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Analyze data and interpret results to inform AI training datasets with precision * Apply ...

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Remote Data Science information

What are the key skills and qualifications needed to thrive as a remote data scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

Can I work remotely as a remote data scientist?

Yes, many remote data scientist positions are available, allowing professionals to work from anywhere with a reliable internet connection. These roles often require skills in programming, data analysis, and familiarity with tools like Python, R, or SQL, and may involve collaboration through online platforms. Remote work arrangements are common in the data science field, especially with the increasing adoption of cloud-based tools and flexible schedules.

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

More about Remote Data Science jobs
What are the most commonly searched types of Data Science jobs in Towson, MD? The most popular types of Data Science jobs in Towson, MD are:
What job categories do people searching Remote Data Science jobs in Towson, MD look for? The top searched job categories for Remote Data Science jobs in Towson, MD are:
What cities near Towson, MD are hiring for Remote Data Science jobs? Cities near Towson, MD with the most Remote Data Science job openings:
Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Towson, MD as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Data Engineer - ML/AI Data Platform (Remote)

FEI Systems

Columbia, MD • On-site, Remote

$111K - $133K/yr

Full-time

Re-posted 3 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.

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