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Principal R Jobs (NOW HIRING)

StateJobsNY

Principal Attorney (52632)

Poughkeepsie, NY · On-site

$130K/yr

Principal Attorneys may also assist in selecting and training new staff, developing and ... Name Eben R. Hill Telephone Fax Email Address MHLS2-HR@nycourts.gov Address Street 600 Old Country ...

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$36.5K

$109.4K

$182K

How much do principal r jobs pay per year?

As of Jun 4, 2026, the average yearly pay for principal r in the United States is $109,393.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $125,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Principal, you need strong leadership abilities, educational expertise, and typically a master's degree in education or educational administration along with state certification. Familiarity with school management systems, curriculum planning tools, and data analysis software is often required. Exceptional interpersonal skills, conflict resolution, and the ability to inspire and communicate a clear vision make someone stand out in this role. These skills and qualities are crucial for fostering a positive school environment, driving academic achievement, and effectively managing staff, students, and resources.

How does a Principal typically collaborate with teachers and support staff to foster a positive school culture?

Principals play a key role in shaping and maintaining a positive school culture by regularly meeting with teachers and support staff, encouraging open communication, and supporting professional development initiatives. They often facilitate team meetings, provide constructive feedback, and create opportunities for staff to share ideas and best practices. By fostering an environment of trust and collaboration, principals help ensure that everyone works together to create a supportive learning environment for students.

What are Principal R engineers?

Principal R engineers are senior-level professionals who specialize in the R programming language, often leading data science, statistical analysis, or software development projects. They are responsible for designing complex data models, guiding teams, and establishing best practices in coding and analytics. Their role often involves mentoring junior staff, contributing to strategic decision-making, and ensuring high-quality results using R. Principal R engineers are recognized for their expertise in both technical and leadership capacities within organizations.

What is the difference between Principal R and Senior R Developer?

AspectPrincipal RSenior R Developer
Required CredentialsAdvanced degrees (Master's/PhD), extensive R expertise, leadership skillsTypically bachelor's or master's degree, strong R programming skills
Work EnvironmentLeadership roles, strategic planning, cross-team collaborationProject-focused, coding, data analysis, mentorship
Employer & Industry UsageResearch institutions, large corporations, consulting firmsTech companies, finance, healthcare, analytics firms

The main difference between Principal R and Senior R Developer lies in their responsibilities and experience level. Principal R roles focus on strategic leadership, advanced research, and guiding teams, while Senior R Developers primarily handle complex coding, data analysis, and project execution. Both roles require strong R programming skills, but Principal R positions demand more experience and a broader scope of influence within organizations.

More about Principal R jobs
What cities are hiring for Principal R jobs? Cities with the most Principal R job openings:
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Principal R jobs near you
Infographic showing various Principal R job openings in the United States as of May 2026, with employment types broken down into 86% Full Time, 12% Part Time, 1% Temporary, and 1% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $109,393 per year, or $52.6 per hour.
Principal Data Scientist, R&D Oncology

Principal Data Scientist, R&D Oncology

J&J Family of Companies

San Diego, CA • On-site, Remote

Other

This job post has expired today. Applications are no longer accepted.

Job description

Principal Data Scientist, R&D Oncology

Johnson & Johnson Innovative Medicine is recruiting for a Principal Data Scientist, R&D Oncology to join our Data Science and Digital Health team (DSDH). This position will be located at one of our offices in either Spring House PA (preferred), Cambridge MA, or San Diego CA (La Jolla area). Consideration may be given for our Titusville and Raritan, NJ locations.

The Principal Data Scientist, R&D Oncology will support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements. This role will focus on applications in Oncology R&D and support data projects from across the business including Clinical, Pre-Clinical, RWD and 'omics platforms. This role will be a leading technical contributor and creative problem solver with developing AI-ready data and other routinely used data applications for Oncology R&D.

Key Responsibilities:

  • Design, develop and maintain data pipelines for acquiring, managing and storing Oncology R&D data from diverse sources (e.g. biomarker labs, real-world data sources, pre-clinical applications)
  • Work closely with Data Science and Oncology R&D partners to understand, document and prioritize business requirements. Translate these business needs in to high quality data products.
  • Work closely with other technical leaders, such as Ontology and Knowledge graph Engineers to design and deliver future-proof, AI-ready data systems aligned with Oncology R&D business needs.
  • Develop Oncology R&D-specific data repositories by implementing standard enterprise-level data models and create new data models as needed. Leverage cloud-based technology platform to accomplish goals, such as building and maintaining data repositories using AWS S3.
  • Create and optimize data flows for structured and unstructured data using technologies such as Python, R, SQL, AWS services and other relevant tools.
  • Implement quality and performance standards and measure KPIs to determine accuracy and consistency
  • Leverage and implement data versioning and lineage tracking to support data traceability, compliance, maintaining documentation for data architectures and workflows.
  • In adherence to internal standards, implement software development best practices such as Code Versioning, DevOps.

Required Qualifications:

  • Advanced degree (Master's or equivalent) in Computer Science, Engineering, Life Sciences, or other relevant field is strongly preferred. (Bachelor's Degree with experience equivalency may be considered.)
  • 3+ years of experience in data engineering, including data modeling and database design, preferably in the healthcare industry
  • Proficiency in data engineering tools such as Python, R and SQL for data processing as well as cloud architecture (e.g. AWS services, Redshift, FSx, Glue, Lambda.
  • Experience with unstructured database technologies (e.g. NoSQL) as well as other database types (e.g. Graph).
  • Strong skills in analysis, problem-solving, organizational change, project delivery, and managing external vendors.
  • Proven record leading improvement initiatives with multi-disciplinary and remote partners.
  • Demonstrated stakeholder management capabilities- including requirements gathering, business analysis and planning. Must have the capacity to translate discussions into user requirements and project plans.
  • Ability to manage a numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
  • Willingness to conduct periodic travel (<15% of time) to conferences and internal meetings.

Preferred Qualifications:

  • Experience with healthcare data standards (e.g. CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM).
  • Exposure to high dimensional data technologies and handling, including imaging.
  • Familiarity with machine learning operations (MLOps) and model deployment.

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