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Remote Topological Data Analysis Jobs in Iowa (NOW HIRING)

Demand.com

Marketing Director (Remote)

Des Moines, IA · Remote

DemandFactor is a data-driven B2B growth and demand-generation company helping brands find, engage ... Manage marketing KPIs, analytics, attribution, and budget * Build and grow the marketing team What ...

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Remote Topological Data Analysis information

What is remote topological data analysis?

Remote topological data analysis refers to the use of topological methods for analyzing data, performed by professionals who work remotely rather than on-site. Topological data analysis (TDA) is a technique in data science that uses concepts from topology, a branch of mathematics, to extract meaningful patterns and structures from complex datasets. Remote TDA specialists utilize tools like persistent homology to identify features such as clusters, holes, or voids in high-dimensional data. They often collaborate with teams virtually, leveraging cloud-based computational resources and software platforms to conduct their analyses. This approach allows organizations to access specialized expertise regardless of geographic location.

What are some typical challenges faced by professionals working in remote topological data analysis roles?

Professionals in remote Topological Data Analysis often encounter challenges related to collaborating across distributed teams, especially when interpreting complex, high-dimensional data. Communication is key, as team members may need to frequently discuss data structures, algorithms, and findings via virtual meetings and shared documentation. Additionally, staying updated on the latest research and software tools in the rapidly evolving field requires proactive self-learning and participation in online communities. Despite these challenges, remote work offers flexibility and the opportunity to collaborate with experts worldwide.

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

To excel as a Remote Topological Data Analyst, you need a robust background in mathematics, particularly topology and data analysis, often supported by an advanced degree in mathematics, statistics, or computer science. Familiarity with programming languages such as Python or R, experience with TDA libraries (like GUDHI or Ripser), and proficiency in data visualization tools are typically required. Strong problem-solving skills, self-motivation, and effective communication are crucial soft skills for collaborating remotely and conveying complex insights to diverse stakeholders. These abilities enable analysts to extract meaningful patterns from high-dimensional data and deliver actionable results in a distributed work environment.

What are popular job titles related to Remote Topological Data Analysis jobs in Iowa?

For Remote Topological Data Analysis jobs in Iowa, the most frequently searched job titles are:

What job categories do people searching Remote Topological Data Analysis jobs in Iowa look for?

The top searched job categories for Remote Topological Data Analysis jobs in Iowa are:

What cities in Iowa are hiring for Remote Topological Data Analysis jobs?

Cities in Iowa with the most Remote Topological Data Analysis job openings:

Remote Topological Data Analysis jobs near you
Infographic showing various Remote Topological Data Analysis job openings in Iowa as of August 2026, with employment types broken down into 63% Full Time, 13% Part Time, 10% Temporary, and 14% Contract. Highlights an 100% Remote job distribution.

Digital Chemistry Specialist - Remote

micro1 AI

Cedar Rapids, IA • Remote

$90 - $120/hr

Part-time

Posted 21 days ago

Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative 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 complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.

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