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Contract Ai Data Annotation Jobs in Puerto Rico (NOW HIRING)

Linguist III

PR · Remote

Write and revise guidelines for human annotation and other AI projects, including but not limited ... for data analysis are a plus. Must be able to independently work through complex requests and ...

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Contract Ai Data Annotation information

What are the key skills and qualifications needed to thrive as a Contract AI Data Annotation Specialist, and why are they important?

To thrive as a Contract AI Data Annotation Specialist, you need attention to detail, familiarity with data labeling concepts, and at least a high school diploma or relevant experience. Proficiency with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth, as well as basic understanding of data formats, is typically required. Strong communication, time management, and the ability to follow precise guidelines help you excel in this role. These skills ensure accurate, high-quality datasets that are critical for training effective AI and machine learning models.

What are some common challenges faced by contract AI data annotators, and how can they be addressed?

Contract AI data annotators often encounter challenges such as maintaining consistency across large datasets, understanding complex labeling guidelines, and meeting tight project deadlines. To address these, it's important to thoroughly review project documentation, participate in onboarding or training sessions, and communicate proactively with project managers or team leads when questions arise. Leveraging annotation tools efficiently and seeking feedback on your work can also help improve accuracy and productivity, making it easier to adapt to varying project requirements.

What is a Contract AI Data Annotation job?

A Contract AI Data Annotation job involves labeling or tagging data, such as images, text, audio, or video, to help train artificial intelligence (AI) and machine learning models. As a contractor, you'll work on specific projects for a set period, rather than as a full-time employee. The work is detail-oriented and may involve tasks like categorizing objects in photos, transcribing audio, or marking up text for sentiment or intent. This role is crucial in ensuring that AI systems learn accurately and perform well. Contract AI data annotators often work remotely and may be paid by the hour or per task.

What is the difference between Contract Ai Data Annotation vs Data Labeler?

AspectContract Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, project-based
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job FocusAnnotating data for AI trainingLabeling data for AI models

Contract Ai Data Annotation and Data Labeler roles are similar, both involve preparing data for AI systems. However, Contract Ai Data Annotation often encompasses a broader range of annotation tasks and may require familiarity with specific tools or platforms. Both roles are essential in AI development and are commonly found in tech industries, with similar work environments and credential requirements.

What are the most commonly searched types of Ai Data Annotation jobs in Puerto Rico? The most popular types of Ai Data Annotation jobs in Puerto Rico are:
What are popular job titles related to Contract Ai Data Annotation jobs in Puerto Rico? For Contract Ai Data Annotation jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Contract Ai Data Annotation jobs in Puerto Rico look for? The top searched job categories for Contract Ai Data Annotation jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Contract Ai Data Annotation jobs? Cities in Puerto Rico with the most Contract Ai Data Annotation job openings:
Infographic showing various Contract Ai Data Annotation job openings in Puerto Rico as of July 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 87% In-person, and 13% Hybrid job distribution.
Sr Data Scientist

Sr Data Scientist

BioPharma Consulting JAD Group

Juncos, PR • On-site

Contractor

Posted 12 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