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Research Scientist Optimization Jobs in Riverside, CA

Sr. Data Scientist

Irvine, CA · On-site

$114K - $220K/yr

Optimization of circuit or device parameters * RF signal modeling and anomaly detection * Root ... Work on both research-oriented prototypes and production-grade deployments. * Stay up-to-date with ...

Sr. Data Scientist

Irvine, CA · On-site

$114K - $220K/yr

Optimization of circuit or device parameters * RF signal modeling and anomaly detection * Root ... Work on both research-oriented prototypes and production-grade deployments. * Stay up-to-date with ...

Bioinformatics Associate I

Irvine, CA · On-site

$75K - $95K/yr

... research and development under the guidance of bioinformatics scientist in developing new microbiome pipelines or applications. Typical tasks include algorithm selection and optimization, database ...

Mentor senior and mid-level data scientists and shape the research to productization handoff with AI/ML Engineers (Applied). Model performance, optimization & process enablement. Guide implementation ...

Showing results 41-60

Research Scientist Optimization information

See Riverside, CA salary details

$52.7K

$135.7K

$181.5K

How much do research scientist optimization jobs pay per year?

As of Sep 14, 2026, the average yearly pay for research scientist optimization in Riverside, CA is $135,747.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,200.00 and $180,500.00 per year, depending on experience, location, and employer.

What does a research scientist in optimization do?

A Research Scientist in Optimization specializes in developing and applying mathematical techniques to improve processes, systems, or algorithms. Their work often involves formulating optimization problems, designing solutions, and collaborating with engineers or data scientists to implement and test their models. These scientists may work in various industries, such as technology, logistics, finance, or manufacturing, to help organizations make better decisions, save resources, or improve performance. Their daily tasks include conducting experiments, analyzing large datasets, and publishing findings in scientific journals.

What are the key skills and qualifications needed to thrive as a research scientist in optimization?

To excel as a Research Scientist in Optimization, you need a strong background in mathematics, computer science, and optimization theory, often supported by a PhD in a related field. Familiarity with programming languages like Python or MATLAB, optimization libraries (e.g., Gurobi, CPLEX), and experience with data analysis tools are typically required. Critical thinking, creativity, and strong communication skills help in formulating novel approaches and presenting complex findings clearly. These skills drive the development of efficient algorithms and solutions, advancing research impact and innovation in the field.

What types of projects and collaborations can a research scientist in optimization expect to be involved in?

As a Research Scientist specializing in Optimization, you can expect to work on projects that involve developing and improving algorithms to solve complex real-world problems in areas such as logistics, supply chain, or machine learning. Collaboration is common, often involving cross-functional teams with data scientists, software engineers, and domain experts to implement and test optimization solutions. You may also contribute to academic publications, attend conferences, and sometimes mentor junior researchers, all while staying current with the latest advancements in optimization techniques.

What is the difference between Research Scientist Optimization vs Data Scientist?

AspectResearch Scientist OptimizationData Scientist
Required CredentialsMaster's or PhD in Operations Research, Mathematics, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, R&D departments, academiaBusiness analytics, tech companies, consulting firms
Industry UsageOptimization problems, algorithm development, mathematical modelingData analysis, predictive modeling, data visualization

Research Scientist Optimization focuses on developing mathematical models and algorithms to solve complex optimization problems, often in research or academic settings. Data Scientists analyze large datasets to extract insights and build predictive models for business decisions. While both roles require strong analytical skills, Research Scientist Optimization emphasizes mathematical and algorithmic development, whereas Data Scientists focus on data analysis and interpretation.

What job categories do people searching Research Scientist Optimization jobs in Riverside, CA look for?

The top searched job categories for Research Scientist Optimization jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Research Scientist Optimization jobs?

Cities near Riverside, CA with the most Research Scientist Optimization job openings:

Scientist, Staff (Machine Learning & Simulations)

Irvine, CA • On-site

$123K - $158K/yr

Full-time

Re-posted 25 days ago


Job description

Position Title: Scientist, Staff

Department:    Algorithm

Reports to:      Algorithm, Senior Manager                

At Enchannel Medical, we’re redefining the boundaries of electrophysiology with our next-generation DePolar™ mapping system and integrated NanoAblate™ PFA platform. Driven by our global mission to enhance the quality-of-life of heart rhythm patients, our discerning technology, paired with our passion for innovation, leads to enduring outcomes.

Position Overview

This Scientist, Staff (Machine Learning & Simulations), will be a key contributor to our algorithm team, working on innovating and developing new research and product features for our cardiac electrophysiology mapping system. They will be responsible for designing, developing, testing, and improving cardiac simulations used for treating cardiac arrhythmia and collaborating closely with a multidisciplinary team to support system integration and product feature advancements. They will have an opportunity to design and build end-to-end solutions.

Duties and Responsibilities   

The following are the major responsibilities needed for the role.  Additional responsibilities, tasks, and duties will be assigned and required as needed.

  • Develop biophysics-based simulations to predict optimal ablation sites.
  • Optimize the simulation compute resources using statistical, machine learning (ML), and optimization techniques to provide real-time feedback.
  • Analyze and interpret complex cardiac signals.
  • Develop innovative simulation solutions and collaborate with cross-functional teams to integrate simulation outcomes into the software stack.
  • Collaborate with the software engineering team to implement algorithms and ML solutions into computationally efficient, “real-time” operations.
  • Evaluation, adoption, and refinement of prototype algorithms developed by our engineers, scientists, and consultants.
  • Maintain, update, and document design requirements throughout the entire system life cycle. 
  • May be required to actively contribute to regulatory filings, patent applications and other industry related publications.
  • Responsible for compliance with quality system procedures and all regulatory requirements.
  • Consistently promote collaboration, positivity, accountability, and resourcefulness.
  • Must demonstrate mutual respect, ongoing communication, and a positive outlook with both internal team members and customers.

Education, Experience and Skills Required

Below are the minimum skills, formal education, certifications or training, and practical experience required to perform the general functions and duties of the role. 

  • 5+ years of related experience and a Bachelor’s and/or Master’s degree, and/or PhD in a scientific/engineering discipline; or equivalent combination of education and experience.
  • Must demonstrate expertise in cardiac electrophysiology, with a strong foundation in applying this knowledge to practical applications.
  • Hand-ON experience working with cardiac simulation tools.
  • Experience with the use of ML in cardiac anatomy and electrophysiology, ECG, unipolar/bipolar electrogram.
  • Strong programming skills in languages such as Python, C++, and MATLAB.
  • Experience with ML libraries such as OpenCV, TensorFlow, and PyTorch.
  • Broad understanding of machine learning, deep learning, and statistical techniques.
  • Strong problem-solving abilities, with the capacity to develop innovative solutions for complex technical challenges.
  • Excellent collaboration skills to work effectively across multidisciplinary teams, including hardware, software, quality, and regulatory groups.
  • Time management and organizational skills to prioritize workload efficiently in a fast-paced startup environment.
  • Exceptional verbal and written communication skills, including the ability to explain highly technical concepts to non-technical audiences.
  • A results-driven mindset, with the ability to adapt quickly to changing project requirements and deliverables.
  • Must be able to understand job duties and responsibilities, have the necessary skills/knowledge and be willing and able to continue learning and growing within the field.
  • Must be skilled at managing a significant workload and obtaining positive results, taking on additional responsibility and managing priorities as needed.
  • Must be accurate, detailed, committed to high quality standards and pro-active in finding solutions to achieve successful outcomes.
  • Strong verbal and written communication skills with the ability to produce accurate, punctual reports/information, as required and thoroughly share information with others. Must be able to read, write and speak effectively.
  • Exceptional listening skills with the ability to seek constructive feedback, build relationships, promote teamwork, and remain flexible and open-minded. Able to quickly adapt to change.
  • Capable of following realistic plans, goal setting, resource management, contingency planning, coordinating, and cooperating with others.
  • Capable of working thoughtfully under pressure and in a timely manner.

Our pay ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum new hire pay for the position located in California. Within the range, individual pay is determined by location, additional factors, including job-related skills, experience, and relevant education or training. 

EnChannel Medical is an E-Verify and equal opportunity employer. We believe in hiring a diverse workforce and sustaining an inclusive, people-first culture. We are committed to non-discrimination on any protected basis, such as disability and veteran status, or any basis covered under acceptable law.

Only qualified candidates will be contacted.