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Data Science Research Jobs in Nevada (NOW HIRING)

micro1 AI

AI Training Specialist - Life Sciences

Reno, NV · Remote

$90 - $120/hr

Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science. * Experience collaborating in multidisciplinary or remote project environments is ...

JT4, LLC

Computer Scientist II

Las Vegas, NV · On-site

Apply principles of computer science, mathematics, statistics, operations research, and engineering to analyze complex operational problems and develop data-driven solutions. * Collect, organize, and ...

JT4 LLC

Computer Scientist II

Las Vegas, NV · On-site

Apply principles of computer science, mathematics, statistics, operations research, and engineering to analyze complex operational problems and develop data-driven solutions. Collect, organize, and ...

Varsity Tutors

College Political Science Tutor

Reno, NV · Remote

$18 - $40/hr

... research design for political science. Guides students through analyzing legislative processes, comparing political systems, evaluating foreign policy decisions, interpreting polling data, and ...

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Data Science Research information

How does a data science researcher typically collaborate with other departments within an organization?

Data Science Researchers frequently work cross-functionally, collaborating with teams such as engineering, product management, and business analytics. They often translate complex research findings into actionable insights, guiding product development or business strategies. Regular meetings, joint project planning, and code reviews are common, ensuring that research outcomes align with organizational goals. Effective communication and teamwork are key to integrating advanced data solutions into real-world applications.

What do data science researchers do?

Data science researchers analyze large datasets to identify patterns, develop models, and generate insights that inform decision-making. They often use programming languages like Python or R, employ statistical methods, and work with machine learning algorithms to solve complex problems. Their work typically involves experimentation, data cleaning, and collaboration with other teams to apply findings effectively.

What is the difference between Data Science Research vs Data Analyst?

AspectData Science ResearchData Analyst
CredentialsTypically requires advanced degrees (Master's or PhD) in Data Science, Statistics, or related fieldsOften requires a Bachelor's or Master's degree in Data Analysis, Statistics, or related areas
Work EnvironmentResearch labs, academic institutions, or R&D departments within companiesBusiness environments, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutions, tech companies focusing on innovationRetail, finance, healthcare, and other industries focusing on data-driven decision making

Data Science Research focuses on developing new algorithms, models, and theories, often in academic or R&D settings. In contrast, Data Analysts primarily interpret existing data to generate reports and insights for business decisions. Both roles require strong analytical skills but differ in scope, goals, and work environment.

What are the key skills and qualifications needed to thrive as a data science researcher, and why are they important?

To thrive as a Data Science Researcher, you need strong analytical skills, expertise in statistics and machine learning, and an advanced degree in a quantitative field such as computer science, mathematics, or engineering. Proficiency with programming languages like Python or R, data visualization tools, and experience using platforms such as TensorFlow or PyTorch is typically required. Curiosity, creativity, and clear communication are essential soft skills for designing research questions, interpreting results, and sharing findings with diverse audiences. These skills and qualities are crucial for driving innovative solutions and impactful insights in data-driven environments.

What is data science research?

Data science research involves using scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Researchers in this field work on developing new data analysis techniques, machine learning models, and data-driven solutions to solve complex problems. The work often includes designing experiments, analyzing large datasets, and publishing findings to advance the understanding of data science methodologies.
What are popular job titles related to Data Science Research jobs in Nevada? For Data Science Research jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Data Science Research jobs in Nevada look for? The top searched job categories for Data Science Research jobs in Nevada are:
Data Science Research jobs near you
Infographic showing various Data Science Research job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

AI Training Specialist - Life Sciences

micro1 AI

Reno, NV • Remote

$90 - $120/hr

Part-time

Posted 11 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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