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Temporary Data Scientist Machine Learning Jobs in Puerto Rico

Amgen

Senior Data Scientist 35431

Juncos, PR

$37 - $43/hr

The ideal candidate will lead projects from concept through execution, leveraging advanced analytics, machine learning, artificial intelligence, and data science methodologies to generate actionable ...

New

Weil Group, Inc

Sr Data Scientist

Juncos, PR

We are seeking an experienced Senior Data Scientist to lead advanced analytics and machine learning initiatives that drive measurable business value. You will bridge the gap between complex datasets ...

Weil Group, Inc.

Sr Data Scientist

Juncos, PR · On-site

We are seeking an experienced Senior Data Scientist to lead advanced analytics and machine learning initiatives that drive measurable business value. You will bridge the gap between complex datasets ...

Weil Group, Inc

Sr Data Scientist

Juncos, PR · On-site

We are seeking an experienced Senior Data Scientist to lead advanced analytics and machine learning initiatives that drive measurable business value. You will bridge the gap between complex datasets ...

Inteldot

Sr Data Scientist 35431

Juncos, PR · On-site

Leading, using and developing data science, machine learning, and artificial intelligence capabilities across commercial organization. * Leading the projects and be part of cross functional teams on ...

CIS International LLC

PR

Leading, using and developing data science, machine learning, and artificial intelligence. capabilities across Amgen's commercial organization. * Leading the projects and be part of cross functional ...

New

Kelly Services

PR

$48/hr

This role drives advanced analytics, machine learning, and AI initiatives across manufacturing and ... Degree on Data Science, Statistics, Data Mining, Applied Mathematics, Engineering, Computer Science ...

Kelly Services

Sr Data Engineer/ Scientist

Juncos, PR

$48/hr

This role drives advanced analytics, machine learning, and AI initiatives across manufacturing and ... Degree on Data Science, Statistics, Data Mining, Applied Mathematics, Engineering, Computer Science ...

Kelly Services

PR

$48/hr

Leading, developing, and applying data science, machine learning, and artificial intelligence capabilities across the commercial organization. * Managing advanced analytics projects end-to-end ...

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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 June 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Temporary. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.

Senior Data Scientist 35431

Amgen

Juncos, PR

$37 - $43/hr

Full-time

Posted 2 days ago

Job description

Title: Senior Data Scientist (Job ID: 35431)

Location: Puerto Rico (Open to Puerto Rico Residents)

Work Schedule: Hybrid | Administrative Shift

Position Type: 1-Year Contract

Openings: 1


Position Summary


Our client is seeking an experienced and innovative Senior Data Scientist to lead advanced analytics initiatives across its Puerto Rico Operations organization. This role will collaborate with cross-functional teams, including Commercial Insights, Manufacturing, Supply Chain, Engineering, Information Systems, Data Management, and external partners to develop data-driven solutions that address complex business challenges.

The ideal candidate will lead projects from concept through execution, leveraging advanced analytics, machine learning, artificial intelligence, and data science methodologies to generate actionable insights and drive measurable business impact. This position requires a strategic thinker who can translate business needs into analytical solutions while effectively communicating results to stakeholders at all levels.


Preferred Qualifications

  • Bachelor's degree in Data Science, Analytics, Software Engineering, Computer Science, or a related field.
  • Proficiency in Python, R, SQL, Power BI, Databricks, or similar analytics and data visualization platforms.
  • Experience with enterprise data platforms, data warehousing concepts, data modeling, and data integration solutions such as Databricks, SAP, MES, Enterprise Data Warehouses (EDW), or equivalent systems.
  • Knowledge of Industry 4.0 technologies, including IoT, digital twins, and real-time analytics platforms.
  • Experience working in biotechnology, pharmaceutical, or highly regulated manufacturing environments.


Key Responsibilities

  • Lead the development and application of data science, machine learning, and artificial intelligence solutions across the organization.
  • Manage advanced analytics projects from initiation through implementation, ensuring delivery of business value and measurable outcomes.
  • Collaborate with cross-functional teams to identify opportunities for leveraging data to solve business problems and optimize operations.
  • Conduct business assessments, including SWOT analyses, to define analytical approaches and recommend data-driven solutions.
  • Design, develop, and deploy predictive models, machine learning algorithms, prototypes, and proof-of-concept solutions using Python and related technologies.
  • Utilize SQL and other database query languages to extract, analyze, and manage large datasets.
  • Partner with stakeholders to define analytical methodologies and translate business requirements into actionable insights.
  • Present findings, recommendations, and project updates to business leaders in a clear, concise, and impactful manner.
  • Develop compelling presentations and data storytelling materials using PowerPoint, Excel, and other business intelligence tools.
  • Ensure compliance with all applicable regulatory, data privacy, security, and governance requirements related to data assets.
  • Drive innovation by identifying and implementing emerging analytics technologies and methodologies.


Education and Experience Requirements


Candidates must meet one of the following combinations of education and experience:

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


Required Skills and Competencies


  • Degree in Data Science, Engineering, Mathematics, Applied Physics, Statistics, Operations Research, or a related quantitative discipline.
  • Proven experience leading analytics projects and delivering end-to-end solutions.
  • Strong knowledge of relational, SQL, graph, and enterprise database technologies.
  • Hands-on programming experience with Python, R, SAS, or similar languages.
  • Experience with machine learning frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, Keras, Spark MLlib, or equivalent technologies.
  • Ability to develop scalable, reusable, and well-structured code in Python, R, Scala, or similar programming languages.
  • Comfortable working in Linux-based environments.
  • Strong analytical thinking, problem-solving, and decision-making capabilities.
  • Exceptional organizational skills with the ability to manage large, complex datasets and multiple priorities simultaneously.
  • Demonstrated ability to collaborate, influence stakeholders, and drive projects to completion across functional teams.
  • Excellent verbal and written communication skills, with the ability to present technical findings to non-technical audiences.
  • Experience working with large-scale data environments and distributed computing technologies such as Spark, Hive, or equivalent platforms.
  • Strong passion for continuous learning and staying current with advancements in data science, machine learning, and artificial intelligence.
  • Prior biotechnology, pharmaceutical, or regulated industry experience is highly preferred.