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Remote Private Equity Data Science Jobs in Nevada

micro1 AI

Cheminformatics Specialist - Remote

Sparks, NV · On-site +1

$90 - $120/hr

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

micro1 AI

Cheminformatics Specialist - Remote

Reno, NV · On-site +1

$90 - $120/hr

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

JLL

Data Collection Specialist II

Las Vegas, NV · Remote

Bachelor's degree (BA/BS) in engineering, construction management, sciences, IT, or related field a ... Remote -Boston, MA, Chicago, IL, Cleveland, OH, Dallas, TX, Indianapolis, IN, JERSEY CITY, NJ, Las ...

micro1 AI

Cheminformatics Specialist - Remote

Reno, NV · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

micro1 AI

Cheminformatics Specialist - Remote

Sparks, NV · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

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All JobsPrivate Equity Data Science JobsRemote Private Equity Data Science JobsRemote Private Equity Data Science Jobs in Nevada

Remote Private Equity Data Science information

What is remote private equity data science?

Remote Private Equity Data Science involves applying data analysis, machine learning, and statistical techniques to support private equity firms in investment decision-making, portfolio management, and risk assessment—all while working remotely. Professionals in this field analyze large datasets, build predictive models, and generate insights to help firms identify valuable investment opportunities and improve operational efficiency. Working remotely allows data scientists to collaborate with global teams and access diverse data sources using cloud-based tools. This role typically requires strong quantitative skills, knowledge of finance, and experience with programming languages such as Python or R.

What are the key skills and qualifications needed to thrive as a remote private equity data scientist?

To thrive as a Remote Private Equity Data Scientist, you need strong quantitative analysis skills, proficiency in statistics, and experience with financial modeling, typically supported by a degree in data science, finance, or a related field. Expertise in programming languages like Python or R, familiarity with machine learning libraries, and experience with data visualization tools and databases are commonly required, as are certifications in data science or finance. Exceptional problem-solving abilities, communication skills, and the capacity to work independently and collaboratively in remote settings set top professionals apart. These skills ensure accurate analysis of investment opportunities, clear insights for decision-makers, and effective teamwork across distributed environments.

What are some of the unique challenges faced by data scientists working remotely in private equity, and how can they be addressed?

Remote data scientists in private equity often encounter challenges such as accessing sensitive financial data securely, collaborating across time zones, and communicating complex analyses to investment teams. To address these, firms typically implement robust cybersecurity protocols, schedule regular virtual meetings to maintain alignment, and use collaborative tools like shared dashboards or project management platforms. Proactively setting clear expectations and maintaining open lines of communication with both technical and non-technical team members are key to success in this fast-paced, data-driven environment.

What is the difference between Remote Private Equity Data Science vs Remote Investment Analyst?

AspectRemote Private Equity Data ScienceRemote Investment Analyst
Required CredentialsDegree in Data Science, Finance, or related fields; proficiency in data analysis toolsDegree in Finance, Economics, or related fields; strong analytical skills
Work EnvironmentCollaborates with data teams, often in tech or finance firms, using data analysis and modelingResearches market trends, evaluates investments, and prepares reports, often in finance firms
Employer & Industry UsagePrivate equity firms, investment funds, consulting firmsAsset management firms, investment banks, hedge funds

Remote Private Equity Data Science focuses on analyzing large datasets to inform investment decisions using advanced analytics, while Remote Investment Analysts evaluate market data and financial reports to recommend investments. Both roles require strong analytical skills but differ in technical focus and daily tasks.

What are the most commonly searched types of Private Equity Data Science jobs in Nevada?

The most popular types of Private Equity Data Science jobs in Nevada are:

What are popular job titles related to Remote Private Equity Data Science jobs in Nevada?

For Remote Private Equity Data Science jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Remote Private Equity Data Science jobs in Nevada look for?

The top searched job categories for Remote Private Equity Data Science jobs in Nevada are:

What cities in Nevada are hiring for Remote Private Equity Data Science jobs?

Cities in Nevada with the most Remote Private Equity Data Science job openings:

Remote Private Equity Data Science jobs near you
Infographic showing various Remote Private Equity Data Science 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.

Medical Microbiology Consultant - Remote

micro1 AI

Reno, NV • Remote

$70 - $90/hr

Part-time

Posted 23 days ago

Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer 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.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.

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