1

Research Scientist Optimization Jobs in Puerto Rico

PR

$89K - $122K/yr

... optimization. * Ability to analyze manufacturing data, identify process trends, and recommend ... an independent research/project team 7. Initiates productive collaborations outside of the ...

Scientist II

Cayey, PR · On-site

  • Medical

  • Life

Works effectively with cross-functional teams (Regulatory, Quality, Procurement, Research ... Optimization. * Familiarity with Microbiological laboratory practices. Knowledge of standard ...

Works effectively with cross-functional teams (Regulatory, Quality, Procurement, Research ... Optimization. * Familiarity with Microbiological laboratory practices. Knowledge of standard ...

PR · On-site

$95K - $165K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

It is not a research role either. Elegance is nice, but a route that runs two hours shorter is ... Forecasting, route and schedule optimization, anomaly detection, siting and expected-performance ...

Senior Engineer 35627

Juncos, PR

$101K - $139K/yr

... lead and support process optimization, troubleshooting, engineering projects, and system ... Ability to apply engineering principles and scientific methods to production and process ...

... R&D, Quality, Operations, and Suppliers to identify, validate, and implement cost optimization ... scientific techniques, procedures and criteria. This includes constructing detailed, accurate ...

Production Lead

Cayey, PR · On-site

$30 - $50/hr

This role focuses on workflow optimization, waste elimination, and the implementation of Lean ... Bachelor's degree in Business Administration, Engineering, or Science OR 6-8 years of leadership ...

Senior Engineer 35449

Juncos, PR

$101K - $139K/yr

Process optimization and troubleshooting. * Technical writing and engineering documentation ... Research * Utilities * Facilities * Quality Assurance * Validation to support equipment ...

next page

Showing results 1-20

Research Scientist Optimization information

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 are popular job titles related to Research Scientist Optimization jobs in Puerto Rico?

For Research Scientist Optimization jobs in Puerto Rico, the most frequently searched job titles are:

What job categories do people searching Research Scientist Optimization jobs in Puerto Rico look for?

The top searched job categories for Research Scientist Optimization jobs in Puerto Rico are:

What cities in Puerto Rico are hiring for Research Scientist Optimization jobs?

Cities in Puerto Rico with the most Research Scientist Optimization job openings:

Sr. Data Scientist 35618

ProQualityNetwork

Juncos, PR

Full-time

Posted 3 days ago

New


Job description

Title: Senior Data Scientist

Location: Juncos, Puerto Rico (Only open to Puerto Rico Residents)

Work Schedule: Onsite | Administrative Shift

Contract: 6 months

Open Positions: 1


Position Summary

Our client is seeking a Senior Data Scientist to lead advanced analytics projects that support business decision-making and operational performance across the Puerto Rico Operations organization.

The selected candidate will collaborate with cross-functional teams, including Commercial Insights, Manufacturing, Supply Chain, Engineering, Data, Information Systems, Service Owners, and external vendors. This role will be responsible for the end-to-end execution of analytical projects, from identifying business needs and developing analytical approaches to building models, generating insights, and presenting actionable recommendations.

The ideal candidate combines strong data science capabilities with an understanding of manufacturing operations, process optimization, resource planning, capacity analysis, and regulated environments.


Key Responsibilities

  • Lead advanced analytics, data science, machine learning, and AI-enabled projects from concept through implementation.
  • Partner with cross-functional stakeholders to identify business needs and translate them into analytical solutions.
  • Develop analytical methodologies, predictive models, prototypes, algorithms, and proof-of-concept solutions using Python and other appropriate technologies.
  • Analyze complex operational and manufacturing datasets to identify trends, patterns, opportunities, and potential risks.
  • Support resource planning, workload modeling, capacity evaluation, process optimization, and operational efficiency initiatives.
  • Apply statistical methods to evaluate process variability, performance trends, capacity, and business outcomes.
  • Work with SQL and other database query languages to extract, transform, and analyze data.
  • Develop data visualizations, dashboards, and presentations that communicate analytical findings clearly to technical and business audiences.
  • Use tools such as Excel, Power BI, Smartsheet, JMP, Minitab, or similar platforms to analyze and visualize data.
  • Collaborate with business partners and technical teams to define requirements and develop practical, data-driven solutions.
  • Independently manage projects with minimal supervision while maintaining clear communication on progress, risks, and results.
  • Conduct structured business assessments, including SWOT analysis when appropriate, and recommend analytical approaches based on business objectives.
  • Create clear and compelling presentations and data-driven stories using PowerPoint and Microsoft Office tools.
  • Support data, validation, and documentation activities in accordance with applicable GMP, regulatory, security, privacy, and data integrity requirements.
  • Participate in activities that may occasionally require support outside the standard administrative schedule.


Preferred Qualifications

Candidates with backgrounds in the following disciplines are preferred:

  • Industrial Engineering
  • Systems Engineering
  • Computer Science
  • Chemical Engineering
  • Biomedical Engineering
  • Biotechnology
  • Manufacturing Engineering
  • Data Science
  • Statistics
  • Mathematics
  • Operations Research
  • A related technical discipline

An engineering background is particularly valuable due to the role's focus on resource planning, workload modeling, capacity evaluation, process optimization, and operational efficiency. Candidates from science or data-focused disciplines may also be considered if they demonstrate relevant experience in data analytics, digital tools, GMP operations, and/or validation support.


Technical & Analytical Skills

The ideal candidate should demonstrate experience or strong capability in several of the following areas:


Data Analytics & Visualization

  • Collecting, organizing, cleaning, analyzing, and interpreting complex datasets.
  • Developing meaningful visualizations, dashboards, and analytical reports.
  • Experience with Excel, Power BI, Smartsheet, JMP, Minitab, or comparable tools.


Programming, Automation & AI

  • Programming experience with Python, R, SAS, or Scala.
  • Familiarity with AI-assisted coding tools, automation, scripting, Power Automate, or digital workflow development.
  • Ability to develop well-structured, reusable code.
  • Experience with machine learning libraries such as scikit-learn, MLlib, Keras, TensorFlow, or PyTorch.
  • Ability to learn and apply new digital technologies to solve business problems.


Databases & Data Engineering

  • Experience working with relational databases and SQL.
  • Knowledge of database structures and other query technologies.
  • Experience working with large datasets.
  • Familiarity with distributed computing technologies such as Spark or Hive is preferred.
  • Exposure to graph databases is a plus.


Statistics & Process Analysis

  • Understanding of basic and applied statistics.
  • Experience evaluating process variability, trends, performance, capacity, and data relationships.
  • Ability to apply analytical methods to operational forecasting, process evaluation, and business decision-making.


GMP & Validation

  • Knowledge of GMP requirements and regulated manufacturing environments.
  • Experience with validation lifecycle activities, protocols, reports, and controlled documentation.
  • Understanding of data integrity, discrepancy follow-up, and compliance-driven execution is preferred.
  • Biotechnology or pharmaceutical industry experience is strongly preferred.


Education & Experience

One of the following combinations is required:

  • Doctorate in Data Science, Business, Statistics, Data Mining, Applied Mathematics, Business Analytics, Engineering, Computer Science, or a related field.
  • Master's degree + 2 years of relevant experience.
  • Bachelor's degree + 4 years of relevant experience.
  • Associate degree + 8 years of relevant experience.
  • High School Diploma/GED + 10 years of relevant experience.


Relevant experience may include data science, business analytics, statistics, data mining, applied mathematics, engineering, computer science, or related analytical disciplines.

Core Competencies

  • Proven ability to lead projects and execute them from initiation through completion.
  • Strong analytical, logical, problem-solving, and decision-making skills.
  • Excellent organization and planning skills, with the ability to manage multiple complex datasets and priorities.
  • Strong stakeholder management and cross-functional collaboration skills.
  • Ability to influence business partners and technical teams to drive analytical initiatives forward.
  • Excellent written and verbal communication skills.
  • Ability to translate complex analytical findings into clear, precise, and actionable business recommendations.
  • Detail-oriented approach with strong technical aptitude.
  • Ability to work independently and take initiative with minimal supervision.
  • Adaptability and willingness to learn emerging technologies and advanced analytics methodologies.
  • Ability to work effectively in a highly regulated pharmaceutical or biotechnology environment.


Work Environment

  • Onsite position in Juncos, Puerto Rico.
  • Administrative shift.
  • Flexibility to provide support outside the standard schedule may be required based on business and project needs.