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Remote Data Analyst Startup Jobs in Nevada (NOW HIRING)

Analyze and interpret small-molecule and drug discovery datasets using advanced computational ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Scope of Work * Analyze and annotate complex biological data sets, focusing on applications ...

This is a rare opportunity to take ownership of operational safety for Vay's remote driving ... Develop and optimize data-driven tools and methods for incident tracking and risk analysis

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Remote Data Analyst Startup information

What is a remote data analyst at a startup?

A Remote Data Analyst at a startup is a professional who collects, processes, and analyzes data to help the company make informed decisions, all while working from a remote location. Their work often involves creating reports, identifying trends, and providing actionable insights to support business growth and strategy. Since startups are fast-paced and dynamic, remote data analysts may also be expected to work with various teams, adapt to changing priorities, and use a wide range of analytical tools. Strong communication and self-motivation skills are essential for success in this role.

What are the key skills and qualifications needed to thrive as a remote data analyst at a startup?

A Remote Data Analyst at a startup requires strong analytical skills, proficiency in statistics, and experience with data visualization, often supported by a degree in a quantitative field. Familiarity with tools like SQL, Python or R, and platforms such as Tableau or Power BI, as well as experience with cloud-based collaboration tools, is typically expected. Outstanding communication, self-motivation, and adaptability are soft skills that help individuals excel in a fast-paced, remote startup environment. These abilities are vital for delivering actionable insights, collaborating effectively with distributed teams, and driving rapid, data-informed decisions.

How do remote data analysts at startups typically collaborate with cross-functional teams despite working remotely?

Remote Data Analysts at startups often work closely with product managers, engineers, and marketing teams through frequent virtual meetings and collaborative tools like Slack, Zoom, and shared dashboards. Effective communication is key, as analysts need to clearly present their findings and translate data insights into actionable recommendations for different teams. The fast-paced startup environment means priorities can shift quickly, so flexibility and proactive engagement are important for staying aligned with the company's goals.

What are the most commonly searched types of Data Analyst Startup jobs in Nevada?

The most popular types of Data Analyst Startup jobs in Nevada are:

What are popular job titles related to Remote Data Analyst Startup jobs in Nevada?

For Remote Data Analyst Startup jobs in Nevada, the most frequently searched job titles are:

What cities in Nevada are hiring for Remote Data Analyst Startup jobs?

Cities in Nevada with the most Remote Data Analyst Startup job openings:

Cheminformatics Specialist - Remote

micro1 AI

Reno, NV • Remote

$80 - $110/hr

Part-time

Posted 16 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.