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Entry Level Remote Data Modeler Jobs in Atlanta, GA

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

100% Remote. Our direct client has an opening for a Power Platform developer 64265 This position is ... Create data models, user interfaces, workflows, and reports * The candidate will collaborate with ...

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This is not an entry-level or general freight-dispatch position. Candidates must have direct ... Strong computer and data-entry skills * Working knowledge of computers, email, printers, and ...

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This is not an entry-level or general freight-dispatch position. Candidates must have direct ... Strong computer and data-entry skills * Working knowledge of computers, email, printers, and ...

New

... data models, and system interactions. - Support the creation of training materials and user ... Flexible/remote work options may be considered with management approval. #HP1

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How It Works You will participate in a remote, flexible project requiring around 20 hours per week. During the engagement, you will build and review financial models, analyze corporate data sets, and ...

New

Be Seen First

How It Works You will participate in a remote, flexible project requiring around 20 hours per week. During the engagement, you will build and review financial models, analyze corporate data sets, and ...

New

Showing results 41-60

Entry Level Remote Data Modeler information

See Atlanta, GA salary details

$9

$56

$79

How much do entry level remote data modeler jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for entry level remote data modeler in Atlanta, GA is $56.46, according to ZipRecruiter salary data. Most workers in this role earn between $50.62 and $65.67 per hour, depending on experience, location, and employer.

What does an entry level remote data modeler do?

An Entry Level Remote Data Modeler assists in designing, creating, and maintaining data models that organize and structure information for companies, typically while working from home. They work closely with data architects and analysts to translate business requirements into technical data structures, such as databases or data warehouses. Their tasks may include creating diagrams, documenting data flows, and ensuring data integrity. This role often requires proficiency in data modeling tools and a basic understanding of databases and data management concepts.

What are the key skills and qualifications needed to thrive as an entry level remote data modeler, and why are they important?

To thrive as an Entry Level Remote Data Modeler, you need foundational knowledge in database concepts, data modeling principles, and a relevant degree in computer science or information systems. Familiarity with tools like ER/Studio, Microsoft Visio, and SQL-based database systems is typically expected. Strong analytical thinking, attention to detail, and effective communication are standout soft skills for this role. These skills and qualities are important because they ensure accurate data structure design, collaboration with remote teams, and successful implementation of data solutions.

What are the typical challenges faced by entry level remote data modelers, and how can they overcome them?

Entry-level remote data modelers often face challenges such as limited access to immediate mentorship, difficulty understanding complex data structures, and ensuring clear communication with distributed teams. To overcome these obstacles, it’s important to proactively seek feedback through regular virtual meetings, utilize collaboration platforms for documentation and model sharing, and participate in online forums or communities for peer support. Building a habit of clear, detailed documentation and asking clarifying questions early can also help navigate the learning curve and contribute effectively to team projects.

What is the difference between Entry Level Remote Data Modeler vs Entry Level Remote Data Analyst?

AspectEntry Level Remote Data ModelerEntry Level Remote Data Analyst
Primary FocusDesigning and developing data models and database structuresAnalyzing data sets to identify trends and generate reports
Required SkillsData modeling, SQL, database design, understanding of data architectureData analysis, Excel, SQL, visualization tools
Work EnvironmentRemote, often collaborating with data engineers and developersRemote, working with business teams and stakeholders
Common CertificationsNone required but beneficial: Microsoft Certified Data Analyst, IBM Data ScienceNone required but beneficial: Microsoft Certified Data Analyst, Google Data Analytics

While both roles are entry-level and often remote, data modelers focus on structuring and designing data systems, whereas data analysts interpret data to support decision-making. Understanding these differences helps job seekers target the right roles based on their skills and career goals.

What are the most commonly searched types of Remote Data Modeler jobs in Atlanta, GA?

The most popular types of Remote Data Modeler jobs in Atlanta, GA are:

What job categories do people searching Entry Level Remote Data Modeler jobs in Atlanta, GA look for?

The top searched job categories for Entry Level Remote Data Modeler jobs in Atlanta, GA are:

Infographic showing various Entry Level Remote Data Modeler job openings in Atlanta, GA as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $117,440 per year, or $56.5 per hour.

Cheminformatics Specialist - Remote

micro1 AI

Atlanta, GA • Remote

$80 - $110/hr

Part-time

Posted 19 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.