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Postdoc Data Science Remote Jobs in Middle River, MD

Lead Data Engineer

Baltimore, MD · On-site +1

$113K - $136K/yr

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field (or ... Work Flexibility This role is eligible for full time remote work.

Senior Data Analyst (Remote)

Baltimore, MD · Remote

$85K - $107K/yr

Bachelor's Degree in Data Science, Mathematics, Computer Science, Statistics, Business or related field OR in lieu of a Bachelor's degree, an additional 4 years of relevant work experience is ...

Senior Data Engineer

Columbia, MD · Remote

$105K - $142K/yr

Location:Fully Remote, United States Position Type: Full-Time Clearance: U.S. citizenship is ... Bachelor's degree in computer science, data science, information systems, engineering, 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 ...

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 ...

Data Engineer

Baltimore, MD · Remote

$100K - $150K/yr

The schedule can be structured rotationally, such as 1-2 weeks onsite followed by 1-2 weeks remote ... Partner with engineers, data scientists, technical teams, and client stakeholders to translate ...

Showing results 21-40

Postdoc Data Science Remote information

See Middle River, MD salary details

$54K

$63.9K

$121.1K

How much do postdoc data science remote jobs pay per year?

As of Sep 12, 2026, the average yearly pay for postdoc data science remote in Middle River, MD is $63,869.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,400.00 and $55,900.00 per year, depending on experience, location, and employer.

What is a postdoc data science remote?

A Postdoc Data Science Remote position is a postdoctoral research role focused on data science, where the work can be performed entirely or mostly from a remote location rather than on-site at a university or research institution. These positions typically involve advanced research in areas such as machine learning, statistics, or computational modeling, and are intended for individuals who have recently completed a PhD. Remote postdoc roles offer flexibility in work location while still providing opportunities to collaborate with academic or industry teams, publish research, and further develop specialized expertise in data science.

What are the key skills and qualifications needed to thrive as a postdoc data science remote?

To thrive as a Postdoc Data Science Remote, you need an advanced degree (typically a Ph.D.) in a quantitative field, strong statistical analysis skills, and proficiency in programming languages such as Python or R. Familiarity with machine learning frameworks, data visualization tools, and cloud computing platforms like AWS or Google Cloud is often required. Excellent problem-solving abilities, self-motivation, and effective communication skills are essential for independent research and collaboration in a remote environment. These competencies enable you to conduct high-level research, contribute valuable insights, and efficiently collaborate with global teams despite working remotely.

What are some typical challenges faced by remote postdoc data scientists when collaborating with research teams?

Remote Postdoc Data Scientists often encounter challenges related to communication and coordination across different time zones and digital platforms. Building rapport and maintaining effective collaboration with interdisciplinary teams can require extra effort, particularly when discussing complex research concepts or troubleshooting data issues. To overcome these hurdles, it’s important to proactively schedule regular virtual meetings, document workflows clearly, and leverage collaborative tools for code and data sharing. Developing strong digital communication skills and being adaptable to various team dynamics are essential for success in this role.

What is the difference between Postdoc Data Science Remote vs Data Scientist?

AspectPostdoc Data Science RemoteData Scientist
Required CredentialsPhD in Data Science, Statistics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentRemote research-focused position, often academic or research institutionRemote or on-site, industry-focused, business or tech company
Employer & Industry UsageUniversities, research labs, academic institutionsTech companies, finance, healthcare, retail, industry
Common Search & ComparisonYesYes

The main difference is that a Postdoc Data Science Remote typically requires a PhD and focuses on research in academic or research settings, whereas a Data Scientist often holds a bachelor's or master's degree and works in industry, applying data analysis to business problems. Both roles may be remote, but their work environments and expectations differ significantly.

What are popular job titles related to Postdoc Data Science Remote jobs in Middle River, MD?

For Postdoc Data Science Remote jobs in Middle River, MD, the most frequently searched job titles are:

Infographic showing various Postdoc Data Science Remote job openings in Middle River, MD as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 71% Full Time, 25% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $63,869 per year, or $30.7 per hour.

Lead Data Engineer

Baltimore, MD • On-site, Remote

T Rowe Price
Funds, Trusts and Financial Programs • 5 - 10K employees

$113K - $136K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


T. Rowe Price rating

9.1

Company rating: 9.1 out of 10

Based on 21 frontline employees who took The Breakroom Quiz


Job description

Role Summary
T. Rowe Price is seeking an experienced Lead Data Engineer to guide the development and deployment of Enterprise data solutions that drives transformation enabling new business capabilities driving growth, tangible operational efficiency, and superior client experiences. The successful candidate will be a hands-on leader with deep technical skills, who can drive best practices and innovation in a collaborative, purpose-driven environment.

Responsibilities

  • Lead the design, development, and maintenance of Enterprise data platform and solutions, analytics capabilities including modernizing data supply chain, integrating advanced data governance capabilities and data distribution patterns.
  • Collaborate with data engineers, business partners, product owners, and other stakeholders to understand business requirements and develop them into robust enterprise data solutions.
  • Modernize legacy ETL capability to data supply chain solution integrating with Enterprise data platform to provide scalability.
  • Modernize legacy data quality, data governance capabilities to innovative enterprise capabilities that can scale.
  • Champion data governance, security, and regulatory compliance, ensuring alignment with T. Rowe Price's standards and industry best practices.
  • Mentor and develop junior engineers, fostering a culture of innovation, diversity, and continuous improvement.
  • Lead offshore team effectively to ensure delivery success aligning to business & strategic objectives.
  • Evaluate and implement emerging technologies, frameworks, and tools to advance T. Rowe Price's data and AI capabilities.
  • Troubleshoot and optimize data solutions and platform performance, ensuring scalability and resilience.
  • Document system architectures, processes, and best practices for technical and non-technical stakeholders.

Qualifications

Required:

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)
  • 8+ years of professional experience in data engineering, AI, or machine learning roles.
  • Strong proficiency in Snowflake tech, DBT, Airflow, Python, Java.
  • Experience with cloud data platforms (AWS, Snowflake), preferably within a regulated industry.
  • Solid understanding of Agile methodologies and DevOps practices.
  • Excellent communication, collaboration, and leadership skills.
  • Knowledge of data privacy, compliance (e.g., GDPR), and industry regulations relevant to financial services.
  • Experience in the asset management or financial services industry.
  • Familiarity with CI/CD pipelines, and model lifecycle management.

Preferred:

  • Industry certifications in cloud or data engineering technologies.
  • Knowledge of data privacy, compliance (e.g., GDPR), and industry regulations relevant to financial services.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for full time remote work.


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