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Entry Level Remote Data Modeler Jobs in Connecticut

micro1 AI

AI Trainer - Microbiology Expert

Stamford, CT · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

AI Trainer - Microbiology Expert

Hartford, CT · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

AI Trainer - Microbiology Expert

Waterbury, CT · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

micro1 AI

AI Trainer - Microbiology Expert

New Haven, CT · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Quora

$139K - $168K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and ... Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ...

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Entry Level Remote Data Modeler information

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 popular job titles related to Entry Level Remote Data Modeler jobs in Connecticut?

For Entry Level Remote Data Modeler jobs in Connecticut, the most frequently searched job titles are:

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

The top searched job categories for Entry Level Remote Data Modeler jobs in Connecticut are:

What cities in Connecticut are hiring for Entry Level Remote Data Modeler jobs?

Cities in Connecticut with the most Entry Level Remote Data Modeler job openings:

Entry Level Remote Data Modeler jobs near you
Infographic showing various Entry Level Remote Data Modeler job openings in Connecticut as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 12% Part Time, 3% Temporary, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Cheminformatics Specialist - Remote

micro1 AI

Hartford, CT • Remote

$80 - $110/hr

Part-time

Posted 18 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.

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