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Senior Data Scientist Jobs in Puerto Rico (NOW HIRING)

Inteldot

Sr Data Scientist 35533

Juncos, PR · On-site

The Data Scientist will lead projects and collaborate with business partners including commercial insights teams, manufacturing, supply chain, engineering, data teams, external vendor partners ...

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Senior Data Scientist information

What are some of the main challenges Senior Data Scientists face when leading cross-functional projects?

Senior Data Scientists often encounter challenges such as aligning project goals across diverse teams, managing expectations of non-technical stakeholders, and ensuring data quality and accessibility. Balancing long-term research initiatives with immediate business needs can also be demanding. Effective communication, project management skills, and the ability to translate complex findings into actionable insights are essential for overcoming these hurdles and driving successful outcomes.

Is 40 too late for data science?

Age is not a barrier to becoming a senior data scientist; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

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

To thrive as a Senior Data Scientist, you need advanced expertise in statistics, machine learning, data analysis, and programming, typically supported by a degree in a quantitative field and several years of experience. Familiarity with tools like Python, R, SQL, cloud platforms, and machine learning frameworks, as well as relevant certifications such as AWS Certified Machine Learning or TensorFlow Developer, is highly valuable. Strong problem-solving abilities, communication skills, and leadership qualities help in translating data insights into actionable business strategies and mentoring junior team members. These skills and qualities are crucial for driving impactful data-driven decisions and fostering innovation within organizations.

What does a senior data scientist make?

A senior data scientist typically earns between $100,000 and $150,000 annually, depending on experience, location, and industry. They often have advanced skills in machine learning, statistical analysis, and programming languages like Python or R, and may also receive bonuses or stock options.

What does a Senior Data Scientist do?

A Senior Data Scientist leads advanced analytical projects, utilizing statistical modeling, machine learning, and data mining techniques to extract insights from large datasets. They collaborate with cross-functional teams to identify business opportunities, design predictive models, and communicate findings to stakeholders. In addition to technical expertise, they often mentor junior data scientists, help define data strategies, and ensure best practices in data analysis and model deployment.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Lead Data Scientist, Chief Data Officer, or Data Science Director, with salaries exceeding $150,000 annually. These roles typically require extensive experience, advanced skills in machine learning and big data tools, and often involve strategic decision-making responsibilities.

What is the difference between Senior Data Scientist vs Data Analyst?

AspectSenior Data ScientistData Analyst
Required CredentialsMaster's or PhD in Data Science, Statistics, or related fieldBachelor's degree in related field, often with certifications
Work EnvironmentAdvanced analytics, modeling, and machine learning projectsData reporting, visualization, and basic analysis
Employer & Industry UsageTech, finance, healthcare, and large enterprisesRetail, marketing, small to medium businesses

While both roles involve working with data, Senior Data Scientists focus on complex modeling and predictive analytics, whereas Data Analysts primarily handle data reporting and visualization. The Senior Data Scientist role requires advanced technical skills and higher education, making it suitable for more complex projects in larger organizations.

What Is a Senior Data Scientist?

A senior data scientist does complex data analysis. Job duties include gathering data and writing reports that can help people make decisions. In some cases, they may offer machine learning which is a way to help computers process and understand data. A senior data scientist may also be asked to formulate an algorithm to solve work problems. You need statistics and programming knowledge to be successful in this career.

More about Senior Data Scientist jobs
What are the most commonly searched types of Data Scientist jobs in Puerto Rico? The most popular types of Data Scientist jobs in Puerto Rico are:
What are popular job titles related to Senior Data Scientist jobs in Puerto Rico? For Senior Data Scientist jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Senior Data Scientist jobs in Puerto Rico look for? The top searched job categories for Senior Data Scientist jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Senior Data Scientist jobs? Cities in Puerto Rico with the most Senior Data Scientist job openings:
What are popular job titles related to Senior Data Scientist jobs in PR? For Senior Data Scientist jobs in PR, the most frequently searched job titles are:
Senior Data Scientist jobs near you
Infographic showing various Senior Data Scientist 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 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