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Data Science Degree Jobs in Puerto Rico (NOW HIRING)

ECHO Consulting Group

Sr Data Scientist

Juncos, PR · On-site

$85 - $120/hr

Skills: * Degree in Data Science, Engineering, Mathematics, Applied Physics, Statistics, or Operations Research * Experience leading the projects and in executions of the projects end to end

Syndeo,-LL

Data Engineer

Carolina, PR · On-site

$65 - $70/hr

Bachelor's Degree in Computer Science, Data Engineering, or a related field * 3+ years of experience in data engineering * Experience with healthcare, RCM, or laboratory data preferred #J-18808 ...

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Data Science Degree information

What is a data science degree?

A Data Science degree is an academic program that prepares students to analyze, interpret, and derive insights from complex data sets using statistical, computational, and machine learning techniques. The curriculum typically includes coursework in mathematics, statistics, computer science, and specialized data science methods. Graduates are equipped with the skills to work in a variety of industries, tackling real-world problems by leveraging data-driven decision making. This degree can be pursued at the undergraduate or graduate level, and often includes hands-on projects and internships.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in mathematics, statistics, and programming, typically supported by a degree in data science, computer science, or a related field. Proficiency in technical tools such as Python or R, SQL, and machine learning frameworks, along with relevant certifications, is highly valued. Strong problem-solving abilities, effective communication, and curiosity help set apart top-performing data scientists. These skills are crucial for extracting actionable insights from data, collaborating with stakeholders, and driving data-driven decision-making.

What types of real-world projects or team collaborations can I expect to work on after earning a data science degree?

After earning a Data Science degree, you can expect to engage in a variety of real-world projects such as building predictive models, analyzing large datasets to uncover business insights, and developing data-driven solutions for organizational challenges. Data scientists often collaborate closely with cross-functional teams, including software engineers, business analysts, and domain experts, to translate complex data findings into actionable strategies. These collaborations not only enhance your technical skills but also provide valuable experience in communication and project management, which are essential for career growth in this field.

What is the difference between Data Science Degree vs Data Analyst?

AspectData Science DegreeData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's in Statistics, Mathematics, or related fields
Work EnvironmentResearch, modeling, developing algorithms, often in tech or finance industriesData cleaning, reporting, visualization, supporting business decisions
Employer & Industry UsageTech companies, finance, healthcare, academiaRetail, marketing, finance, healthcare

Data Science Degree programs focus on advanced analytics, machine learning, and programming, preparing individuals for complex modeling roles. Data Analysts typically handle data processing, visualization, and reporting to support decision-making. While both roles require strong analytical skills, Data Science degrees emphasize technical and statistical expertise, whereas Data Analysts focus on interpreting data for business insights.

What can I do with my data science degree?

A data science degree prepares individuals for roles such as data analyst, data scientist, machine learning engineer, and business intelligence analyst. Graduates can work in industries like technology, finance, healthcare, and marketing, utilizing skills in programming, statistical analysis, and data visualization tools like Python, R, and SQL.

What jobs can a data science degree get?

A data science degree qualifies individuals for roles such as data analyst, data scientist, machine learning engineer, and business intelligence analyst. These positions typically require skills in programming, statistical analysis, and data visualization tools like Python, R, or SQL, and may involve working in various industries including technology, finance, healthcare, and marketing.

What are popular job titles related to Data Science Degree jobs in Puerto Rico?

For Data Science Degree jobs in Puerto Rico, the most frequently searched job titles are:

What job categories do people searching Data Science Degree jobs in Puerto Rico look for?

The top searched job categories for Data Science Degree jobs in Puerto Rico are:

What cities in Puerto Rico are hiring for Data Science Degree jobs?

Cities in Puerto Rico with the most Data Science Degree job openings:

Data Science Degree jobs near you

Sr Data Scientist

BioPharma Consulting JAD Group

Juncos, PR • On-site

$110 - $170/hr

Other

Re-posted 23 days ago

Job description

The Senior Data Scientist leads advanced analytics initiatives and collaborates with cross‑functional partners—including commercial insights, manufacturing, supply chain, engineering, data teams, external vendors, service owners, and information systems—to develop analytical models and insights that solve complex business problems. This role drives end‑to‑end execution of data science projects, builds high‑impact analytical solutions, and delivers measurable business value through machine learning, artificial intelligence, and statistical modeling.

KEY RESPONSIBILITIES
  • Lead, design, and develop data science, machine learning, and AI capabilities across the organization.
  • Build high‑performance algorithms, prototypes, predictive models, and proof‑of‑concepts using Python and modern ML libraries.
  • Work with SQL and other database query languages to extract, transform, and analyze large datasets.
  • Apply statistical and analytical techniques to evaluate process variability, performance trends, capacity, and operational efficiency.
  • Lead cross‑functional analytics projects from concept to deployment with minimal supervision.
  • Identify business needs, conduct SWOT analyses, propose analytical approaches, obtain stakeholder alignment, and execute solutions end‑to‑end.
  • Manage multiple complex datasets, ensuring accuracy, consistency, and data integrity.
  • Ensure compliance with regulatory, security, and privacy requirements related to data assets.
  • Partner with manufacturing, supply chain, engineering, validation, quality, and digital/IS teams to develop methodologies that address specific business questions.
  • Gather user requirements, translate business needs into analytical or digital tool specifications, and communicate findings clearly to technical and non‑technical stakeholders.
  • Collaborate with external vendors and digital partners to support model development, automation, and system integration.
  • Present analytical concepts, project progress, and results in a clear, compelling, and actionable manner.
  • Create strong data‑driven narratives using PowerPoint, Excel, Power BI, Smartsheet, or similar visualization tools.
  • Develop dashboards, reports, and visualizations to support decision‑making across operations.
  • Support characterization, validation, and GMP‑related data evaluation activities.
  • Apply statistical thinking to workload forecasting, resource planning, capacity modeling, and operational optimization.
  • Support documentation practices, protocol/report development, discrepancy follow‑up, and compliance‑driven execution.
CORE COMPETENCIES & SKILLS
  • Strong foundation in data science, machine learning, and AI methodologies.
  • Proficiency in Python, R, SAS, and ML libraries (scikit‑learn, TensorFlow, Keras, PyTorch, etc.).
  • Experience with relational, SQL, and graph databases.
  • Ability to write clean, reusable, well‑abstracted code; comfortable working in Linux environments.
  • Experience with distributed computing tools (Spark, Hive, etc.).
  • Excellent analytical, logical reasoning, and problem‑solving skills.
  • Strong organizational and planning skills; ability to manage large datasets and multiple projects.
  • Excellent communication skills with the ability to translate complex analysis into actionable insights.
  • Passion for continuous learning and staying current with advanced analytics trends.
  • Experience in biotech/pharma or regulated environments is a plus.
EDUCATION REQUIREMENTS

One of the following is required:

  • Doctorate, OR
  • Master’s degree + 2 years of relevant experience, OR
  • Bachelor’s degree + 4 years of relevant experience, OR
  • Associate degree + 8 years of relevant experience, OR
  • High school/GED + 10 years of relevant experience.

Relevant fields include: Data Science, Statistics, Data Mining, Applied Mathematics, Business Analytics, Engineering, Computer Science, or related technical disciplines.

PREFERRED QUALIFICATIONS
  • Strong data analytics and visualization skills using Excel, Power BI, Smartsheet, JMP, Minitab, or similar tools.
  • Ability to collect, clean, organize, analyze, and interpret complex operational or manufacturing datasets.
  • Experience with automation or digital tools (Python scripting, AI‑assisted coding, Power Automate, workflow development).
  • Understanding of basic statistics, process variability, trending, capacity evaluation, and performance monitoring.
  • Experience supporting characterization, validation, or GMP‑related data evaluation.
  • Familiarity with validation lifecycle activities, protocol/report development, documentation practices, data integrity, and compliance expectations.
  • Strong stakeholder engagement skills; ability to gather requirements and communicate findings clearly to management and technical teams.
  • Ability to work across manufacturing, engineering, quality, supply chain, and digital functions.
  • 6- month contract with possible extension
  • Administrative Shift
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