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Remote Hedge Fund Data Engineer Jobs in Michigan

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Remote Hedge Fund Data Engineer information

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.
What are the most commonly searched types of Hedge Fund Data Engineer jobs in Michigan? The most popular types of Hedge Fund Data Engineer jobs in Michigan are:
What are popular job titles related to Remote Hedge Fund Data Engineer jobs in Michigan? For Remote Hedge Fund Data Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Hedge Fund Data Engineer jobs in Michigan look for? The top searched job categories for Remote Hedge Fund Data Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Hedge Fund Data Engineer jobs? Cities in Michigan with the most Remote Hedge Fund Data Engineer job openings:
Remote Hedge Fund Data Engineer jobs near you
Infographic showing various Remote Hedge Fund Data Engineer job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Scientist - Materials R&D - Remote-Travel

Intertape Polymer Group (IPG)

Marysville, MI • On-site, Remote

Full-time

Re-posted 26 days ago

Intertape Polymer Group rating

6.9

Company rating: 6.9 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

73rd of 119 rated packaging manufacturers

Job description

Join the IPG Team!
Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutions-we are a community that values safety, people, passion, integrity, performance, and teamwork. From tapes and films to packaging and protective products, as well as engineered coated materials and advanced packaging machinery, we develop innovative solutions that protect the world. Now, we are expanding our global team and looking for talented individuals like you!
This position can be based out of Marysville, MI, or work remotely with some travel as needed.
Title: Senior Data Scientist
Department: Research and Development
Immediate Supervisor: R&D Vice President
Status: Exempt Salaried
Position Purpose: The Senior Data Scientist willsupport R&D efforts in bio-polymers and sustainable materials and focusing on applying advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles.
Principle Accountabilities
  • Partner with polymer scientists, chemists, and engineers to support bio-polymer research and development using data-driven methods
  • Analyze and model experimental, formulation, and process data to identify structure-property-process relationships
  • Develop predictive models to support:
    • Material performance and property optimization
    • Formulation design and screening
    • Scale-up and process optimization
  • Design and analyze experiments (DOE) to maximize learning efficiency and reduce development timelines
  • Build and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysis
  • Apply machine learning techniques (e.g., regression, classification, clustering, time-series modeling) to complex scientific datasets
  • Collaborate with data engineering and IT teams to enable scalable data infrastructure for R&D
  • Communicate insights, tradeoffs, and recommendations clearly to technical and non-technical stakeholders
  • Understanding of data visualization best practices
  • Experience working with batch or streaming data processes a plus
  • Contribute to data dictionaries and process flow diagrams for complex data solutions
  • Mentor junior data scientists or technical staff and contribute to data science best practices within R&D
  • Stay current with advances in materials informatics, polymer modeling, and applied AI in scientific research

Essential Skills and Experience
  • Bachelor's degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Master's or PhD preferred
  • 10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, preferred
  • Strong proficiency in Python and/or R for data analysis and modeling
  • Solid experience with SQL and working with structured and semi-structured datasets
  • Strong foundation in statistics, experimental design, and multivariate analysis
  • Demonstrated experience applying machine learning to real-world, noisy scientific or experimental data
  • Ability to work effectively in a cross-functional R&D environment
  • Strong communication skills with the ability to translate complex analyses into actionable insights
  • Familiarity with bio-polymers, sustainable materials, or polymer processing, preferred
  • Experience with DOE software, laboratory data management systems (LIMS), or scientific databases, preferred
  • Experience deploying models to support R&D decision-making or manufacturing scale-up, preferred
  • Familiarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools, preferred
  • Prior experience mentoring or leading technical projects, preferred

Why Choose IPG?
At IPG, you will find more than just a job-you will find a place where your success is our success. We pride ourselves on a culture built around strong relationships, where every team member plays a crucial role in our growth. Whether it is through cross-department collaboration, continuous training, or sustainability-driven initiatives, we create an environment where you can thrive.
Our commitment to sustainability influences everything we do, from designing eco-friendly products to minimizing waste in our production processes. We are dedicated to building a greener future while providing safe, supportive workplaces for our people.
With over 40 years of industry expertise and a proven track record of growth and innovation, IPG offers a stable, secure environment where you can flourish!
We offer competitive pay, extensive benefits that support you and your family, and exciting career development opportunities. Whether you are looking to enhance your skills or advance your career, we offer ongoing training and the support you need to succeed. Think big, dream bigger, and make an impact with IPG.
You belong here. Join us today!

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