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Remote Data Analyst Fintech Jobs in Nevada (NOW HIRING)

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 ...

Project Talent Model (PTM) is a model that is tailored specifically for long-term, remote client ... software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by ...

Data Center COE Project Manager

NV ยท Remote

$112K/yr

Remote in the US #LI-Remote This role is contributing to the Electrification Services Business Area ... Analyzing and addressing project risks, and regularly disseminating lessons learned * Working with ...

Stop Loss Underwriter

Las Vegas, NV ยท On-site +1

$65K - $85K/yr

Remote (United States) About Acrisure A global fintech leader, Acrisure empowers millions of ... Analyze renewal performance and determine rate adjustments * Balance competitiveness with ...

Showing results 41-60

Remote Data Analyst Fintech information

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

To thrive as a Remote Data Analyst in Fintech, you need strong analytical abilities, proficiency in statistics, and a background in finance, typically supported by a relevant degree. Expertise in technical tools such as SQL, Python, data visualization platforms (e.g., Tableau), and experience with financial modeling or risk analysis systems are often required. Strong problem-solving skills, attention to detail, and effective remote communication make candidates stand out in this role. These skills are crucial for delivering accurate data-driven insights that support financial decision-making and regulatory compliance in a fast-evolving industry.

How does a remote data analyst in fintech typically collaborate with cross-functional teams?

As a Remote Data Analyst in fintech, you will regularly collaborate with product managers, engineers, and business analysts through virtual meetings and digital project management tools. Clear communication is essential, as you'll often translate complex data findings into actionable insights for non-technical stakeholders. Collaboration usually involves participating in sprint meetings, sharing dashboards, and providing real-time data support to optimize product features or enhance risk assessment processes. Building strong remote working relationships is key to ensuring alignment and timely delivery of analytics solutions.

What is the difference between Remote Data Analyst Fintech vs Remote Data Analyst Banking?

AspectRemote Data Analyst FintechRemote Data Analyst Banking
CredentialsBachelor's in Data Science, Finance, or related fields; certifications like CFA or Microsoft Data certificationsBachelor's in Finance, Economics, or Data Science; similar certifications often preferred
Work EnvironmentStartups, tech companies, online platforms in financial technologyTraditional banks, financial institutions, online banking services
Industry UsageUsed in innovative financial apps, digital payment platforms, and online lendingApplied in retail banking, investment banking, and financial services

The main difference between a Remote Data Analyst Fintech and a Remote Data Analyst Banking lies in their industry focus. Fintech analysts work primarily with innovative financial technology companies, while banking analysts are employed within traditional banking institutions. Both roles require similar skills and certifications but differ in work environment and industry applications.

What does a remote data analyst in fintech do?

A Remote Data Analyst in Fintech is responsible for collecting, processing, and analyzing financial data to help companies make informed business decisions. They work with large datasets, identify trends, and generate actionable insights to improve financial products or services. This role often requires proficiency in data analysis tools, strong statistical skills, and an understanding of financial markets or payment systems. As the position is remote, communication and collaboration are typically conducted online using digital tools.
What are the most commonly searched types of Data Analyst Fintech jobs in Nevada? The most popular types of Data Analyst Fintech jobs in Nevada are:
What job categories do people searching Remote Data Analyst Fintech jobs in Nevada look for? The top searched job categories for Remote Data Analyst Fintech jobs in Nevada are:
What cities in Nevada are hiring for Remote Data Analyst Fintech jobs? Cities in Nevada with the most Remote Data Analyst Fintech job openings:
Infographic showing various Remote Data Analyst Fintech job openings in Nevada as of August 2026, with employment types broken down into 80% Full Time, 5% Temporary, and 15% Contract. Highlights an 100% Remote job distribution.

Digital Chemistry Specialist - Remote

micro1 AI

Las Vegas, NV โ€ข Remote

$90 - $120/hr

Part-time

Posted 9 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 โ€” 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.