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Remote Hedge Fund Data Engineer Jobs in Stuart, FL

ITW Avery Weigh-Tronix

Dillon Product Manager

FL · Remote

$80K - $121K/yr

The Dillon Product Manager will partner with marketing and engineering teams to help design product ... Perform product testing, gathering of relevant experimental data, and data analysis in support of ...

Careficient

Senior Database Administrator

Stuart, FL · On-site +1

$44 - $60.50/hr

... data lake architecture. This person will work with a Director of IT and Senior Software Engineers ... BENEFITS Fully remote position - applicants must reside and be authorized to work in the U.S.

All JobsHedge Fund Data Engineer JobsRemote Hedge Fund Data Engineer JobsRemote Hedge Fund Data Engineer Jobs in Stuart, FL

Remote Hedge Fund Data Engineer information

See Stuart, FL salary details

$39.3K

$114.5K

$156.7K

How much do remote hedge fund data engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for remote hedge fund data engineer in Stuart, FL is $114,501.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,100.00 and $121,400.00 per year, depending on experience, location, and employer.

What is the difference between Remote Hedge Fund Data Engineer vs Remote Quantitative Analyst?

AspectRemote Hedge Fund Data EngineerRemote Quantitative Analyst
Required CredentialsBachelor's in Computer Science, Data Science, or related field; experience with data engineering toolsBachelor's or higher in Mathematics, Statistics, or related; programming skills in Python, R
Work EnvironmentFinancial firms, hedge funds, or asset management companies; focus on data pipelinesResearch firms, hedge funds, or investment banks; focus on modeling and analysis
Employer & Industry UsageCommonly employed in hedge funds for data infrastructureUsed for developing trading strategies and risk models in finance

The main difference is that Remote Hedge Fund Data Engineers focus on building and maintaining data systems, while Remote Quantitative Analysts develop models and strategies. Both roles require strong analytical skills, but their daily tasks and focus areas differ within the hedge fund industry.

What does a remote hedge fund data engineer do?

A Remote Hedge Fund Data Engineer is responsible for designing, building, and maintaining data pipelines and infrastructure that support the data needs of a hedge fund, all while working from a remote location. They collect, process, and analyze large volumes of financial and market data to enable investment strategies and decision-making. This role often involves working with modern data technologies, ensuring data quality, and collaborating with portfolio managers, analysts, and other engineers. Remote Data Engineers must also ensure secure and efficient data flow, troubleshoot issues, and optimize data systems for performance.

What are the key skills and qualifications needed to thrive as a remote hedge fund data engineer?

To thrive as a Remote Hedge Fund Data Engineer, you need strong programming skills (typically in Python, SQL, or Java), a solid understanding of financial data structures, and a degree in computer science, engineering, or a related field. Expertise in cloud platforms (such as AWS or Azure), data pipeline tools (like Apache Spark or Airflow), and experience with big data technologies are commonly required, along with relevant certifications. Exceptional analytical thinking, attention to detail, and clear communication help you proactively solve complex problems and collaborate effectively with distributed teams. These skills are crucial for ensuring the timely, accurate, and secure processing of large-scale financial data that drives investment decisions.

How does a remote hedge fund data engineer typically collaborate with portfolio managers and quantitative analysts?

As a Remote Hedge Fund Data Engineer, you will frequently work alongside portfolio managers and quantitative analysts to ensure access to timely, high-quality data for investment decision-making. Collaboration often involves gathering requirements for new data sources, supporting the development and maintenance of data pipelines, and troubleshooting data quality issues. Effective communication is essential, as you'll need to translate business needs into technical solutions and provide ongoing support for data-driven strategies, all while working within a distributed team environment. Regular virtual meetings, shared documentation, and version control tools help maintain alignment and foster a collaborative workflow.
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Remote Hedge Fund Data Engineer jobs near you

Digital Chemistry Specialist - Remote

micro1 AI

Port Saint Lucie, FL • Remote

$90 - $120/hr

Part-time

Posted 13 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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