ZipRecruiter

Log In

1

Temporary Data Scientist Machine Learning Jobs in Puerto Rico

Inteldot

Sr Data Scientist 35533

Juncos, PR · On-site

The Data Scientist will lead projects and collaborate with business partners including commercial ... Knowledge of Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs)

next page

Showing results 1-20

All JobsData Scientist Machine Learning JobsTemporary Data Scientist Machine Learning JobsTemporary Data Scientist Machine Learning Jobs in Puerto Rico

Temporary Data Scientist Machine Learning information

What is the difference between Temporary Data Scientist Machine Learning vs Temporary Data Analyst?

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

What does a Temporary Data Scientist specializing in Machine Learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a Temporary Data Scientist Machine Learning, and why are they important?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary Data Scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.
What are popular job titles related to Temporary Data Scientist Machine Learning jobs in Puerto Rico? For Temporary Data Scientist Machine Learning jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Temporary Data Scientist Machine Learning jobs in Puerto Rico look for? The top searched job categories for Temporary Data Scientist Machine Learning jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Temporary Data Scientist Machine Learning jobs? Cities in Puerto Rico with the most Temporary Data Scientist Machine Learning job openings:
Temporary Data Scientist Machine Learning jobs near you
Infographic showing various Temporary Data Scientist Machine Learning job openings in Puerto Rico as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.
Sr Data Scientist

Sr Data Scientist

BioPharma Consulting JAD Group

Juncos, PR • On-site

Contractor

Posted 13 days ago

Job description

The Sr. Data Scientist will lead advanced analytics initiatives and partner with cross‑functional teams—including Commercial Insights, Manufacturing, Supply Chain, Engineering, Data Teams, External Vendors, Service Owners, and IS partners—to design and implement analytical models that solve complex business challenges across the PR Operations Organization. This role is responsible for end‑to‑end project execution, from problem definition and methodology selection to model development, deployment, and communication of insights. The Sr. Data Scientist will drive innovation and deliver measurable business impact through strategic use of data science, machine learning, and artificial intelligence.

Key Responsibilities

  • Lead, develop, and apply data science, machine learning, and AI capabilities across operational and commercial functions.
  • Serve as project lead within cross‑functional teams to generate insights that deliver substantial business value.
  • Work independently with minimal supervision, proactively identifying analytical opportunities.
  • Conduct business needs assessments, perform SWOT analyses, propose analytical approaches, secure stakeholder alignment, and execute projects end‑to‑end.
  • Build high‑performance algorithms, prototypes, predictive models, and proof‑of‑concepts using Python.
  • Develop and execute SQL and other database queries across relational and graph databases.
  • Collaborate with stakeholders to define methodologies and analytical frameworks that address specific business questions.
  • Present analytical concepts, project updates, and results in a clear, compelling, and actionable manner.
  • Create strong data‑driven narratives and presentations using PowerPoint; demonstrate proficiency in Excel and the MS Office suite.
  • Ensure compliance with regulatory, security, and privacy requirements related to data assets.

Skills

  • Background in Data Science, Engineering, Mathematics, Applied Physics, Statistics, or Operations Research.
  • Proven experience leading and executing analytics projects end‑to‑end.
  • Strong experience with relational, SQL, and graph databases.
  • Programming proficiency in Python, R, or SAS; familiarity with ML libraries such as scikit‑learn, MLlib, Keras, TensorFlow, PyTorch, etc.
  • Ability to write well‑abstracted, reusable code; comfortable working in Linux environments.
  • Strong logical reasoning, problem‑solving, and decision‑making skills.
  • Excellent organizational skills and ability to manage large, complex datasets.
  • Ability to collaborate and influence cross‑functional partners to drive analytics initiatives.
  • Exceptional communication skills with the ability to translate complex analysis into clear, actionable insights.
  • Experience with distributed computing tools (Spark, Hive, etc.) and large‑scale data environments.
  • Passion for continuous learning and staying current with advanced analytics trends.
  • Experience in biotech or pharmaceutical environments preferred.

Requirements

Required Education & Experience

  • Doctorate OR
  • Master’s + 2 years of experience in data science, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or related fields OR
  • Bachelor’s + 4 years of experience in related fields OR
  • Associate’s + 8 years of experience in related fields OR
  • High School/GED + 10 years of experience in related fields

Highly Preferred:

  • Degree in Computer Engineering or Computer Science
  • Specialized courses or certifications in Artificial Intelligence / Machine Learning

Preferred Qualifications

  • Experience supporting manufacturing operations; vial filling experience highly preferred.
  • Experience deploying or integrating AI solutions into manufacturing or operational environments.
  • Strong foundation in artificial intelligence, software development, and digital technologies.
  • Hands‑on experience developing AI/ML models for process optimization or task automation.
  • Knowledge of Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs).
  • Experience with Python, TensorFlow, PyTorch, OpenCV, or similar AI/ML frameworks.
  • Basic statistical analysis skills using JMP or similar tools.
  • Experience generating technical documentation, protocols, reports, and development records.
  • Knowledge of Good Documentation Practices (GDP), quality systems, and compliance requirements.
  • Strong project management and problem‑solving capabilities.
  • Ability to communicate effectively with both technical and non‑technical stakeholders.
  • Quality‑focused mindset with strong attention to detail.
  • High digital literacy and proficiency with AI tools and modern technologies.

Benefits

  • 5-month contract with possible extension
  • Administrative Shift