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Freelance R Shiny Developer Jobs in California (NOW HIRING)

Experience with interactive visualization tools and report generation frameworks such as Shiny ... Strong programming proficiency in Python or R, with demonstrated experience using AI coding ...

Shiny apps) for routine data analysis (e.g. RNAseq profiling) for team members • Perform routine ... GCP) with appropriate engineering adaptations as needed. Help develop and work within budgets for ...

... R and sync teams, songwriters, and producers. You will identify opportunities to integrate WCM ... A network of highly-skilled freelance music professionals (composers, musicians, engineers, editors ...

... R and sync teams, songwriters, and producers. You will identify opportunities to integrate WCM ... A network of highly-skilled freelance music professionals (composers, musicians, engineers, editors ...

Senior Scientist, Bio AI

Redwood City, CA · On-site

$205K - $235K/yr

Shiny apps) for routine data analysis (e.g. RNAseq profiling) for team members * Perform routine ... GCP) with appropriate engineering adaptations as needed. Help develop and work within budgets for ...

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Freelance R Shiny Developer information

What are the key skills and qualifications needed to thrive as a Freelance R Shiny Developer, and why are they important?

To thrive as a Freelance R Shiny Developer, you need strong proficiency in R programming, Shiny app development, and a solid understanding of data analysis or statistics, often supported by a degree in a quantitative field. Familiarity with version control systems (like Git), cloud deployment platforms, and knowledge of relevant R packages are typically required. Excellent problem-solving, communication, and client management skills set successful freelancers apart. These skills and qualities are essential for delivering effective, user-friendly applications and maintaining strong client relationships in a competitive freelance market.

What are some common challenges faced by freelance R Shiny developers when working with clients remotely?

Freelance R Shiny developers often encounter challenges such as clearly understanding client requirements, managing communication across different time zones, and ensuring that the application meets both technical and business needs. Since projects are typically remote, it is important to establish regular check-ins, use collaborative tools for feedback, and maintain thorough documentation. Additionally, balancing multiple projects and staying updated on the latest R Shiny features can be demanding, but these practices help ensure successful project delivery and client satisfaction.

What are Freelance R Shiny Developers?

Freelance R Shiny Developers are independent professionals who design, build, and maintain interactive web applications using R and the Shiny framework. They typically work on a contract or project basis for various clients, helping to transform data analysis and statistical models into user-friendly dashboards and tools. Their responsibilities may include data visualization, UI/UX design, deploying Shiny apps, and integrating them with other technologies. Since they work freelance, they often manage multiple projects and clients simultaneously, offering flexibility and specialized expertise.

What is the difference between Freelance R Shiny Developer vs Data Analyst?

AspectFreelance R Shiny DeveloperData Analyst
Required SkillsProficiency in R, Shiny, web app developmentData manipulation, visualization, statistical analysis
Work EnvironmentIndependent, project-based, remote or on-siteCorporate or organizational settings, often full-time
CertificationsR programming, Shiny development experienceData analysis, statistics, or related certifications
Industry UsageTech, healthcare, finance, research projectsBusiness intelligence, market research, reporting

While both roles involve working with data, a Freelance R Shiny Developer specializes in creating interactive web applications using R and Shiny, often on a project basis. A Data Analyst focuses on interpreting data, generating reports, and providing insights within organizations. The developer role emphasizes technical web app skills, whereas the analyst role centers on data interpretation and communication.

What are the most commonly searched types of R Shiny Developer jobs in California? The most popular types of R Shiny Developer jobs in California are:
What job categories do people searching Freelance R Shiny Developer jobs in California look for? The top searched job categories for Freelance R Shiny Developer jobs in California are:
What cities in California are hiring for Freelance R Shiny Developer jobs? Cities in California with the most Freelance R Shiny Developer job openings:
Infographic showing various Freelance R Shiny Developer job openings in California as of May 2026, with employment types broken down into 40% Internship, 40% Full Time, and 20% Part Time. Highlights an 40% In-person, and 60% Remote job distribution.
Senior Data Scientist - AI

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 hours ago


Job description

Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.

Arrowhead Intermediaries is looking for a Senior Data Scientist to join our Data & Analytics Team!

Join us as a Senior Data Scientist, with a strong focus on how AI and large language models can help a business win - not just how to run a better model. You are comfortable bridging the gap between cutting-edge technology and practical business constraints, asking questions that actuaries, underwriters, and business leaders haven't thought to ask yet, and finding ways to answer them. You take ownership of outcomes and not just outputs. This is an opportunity to shape how a leading global insurance intermediary thinks about AI-driven underwriting that improves risk selection, enhances pricing models, and drives profitability across our property and casualty insurance products.

You will use generative AI as a force multiplier - enabling you to independently prototype data pipelines, unlock alternative data sources, and deliver end-to-end solutions that would traditionally require multiple engineering handoffs. You are proactively identifying where AI can move the needle on underwriting profitability and risk selection.

Most importantly, you are a team player. You value working in a collaborative environment, helping others succeed and contributing to shared outcomes with humility, curiosity, and clear communication.

JOB DUTIES:

  • Identify, extract, and integrate non-traditional data sources into underwriting and pricing workflows using generative AI, LLMs, and AI-assisted pipeline development
  • Prototype, build, and iterate on data enrichment pipelines rapidly, validating signal quality and relevance before integration into production models - expanding the team's data capabilities without traditional engineering dependencies.
  • Design, build, and maintain advanced predictive models for risk frequency, severity, and loss ratio that directly inform point-of-sale underwriting decisions.
  • Collaborate closely with actuaries and fellow data scientists to ensure all models are actuarially sound, statistically defensible, and aligned with pricing objectives.
  • Own models end-to-end - from hypothesis formation and data collection through to production deployment and ongoing monitoring.
  • Apply the latest generative AI tools, agentic frameworks, and LLM capabilities to real underwriting and pricing problems - staying current on developments and evaluating new approaches proactively.
  • Ensure all solutions are maintainable, well-documented, and consistent with established team standards for reproducibility and deployment.
  • Partner directly with underwriters and business leaders to understand portfolio needs, translate business problems into analytical solutions, and communicate findings clearly to non-technical stakeholders.
  • Serve as a technical authority and mentor for the broader data science team - elevating the team's fluency in generative AI tooling and best practices.
  • Contribute to a collaborative, standards-driven team environment where your work can be maintained and built upon by others.

Basic Qualifications:

  • 5+ years of experience in data science or applied machine learning, with demonstrated end-to-end model ownership from data collection through production deployment. You can lead projects independently while keeping stakeholders aware of progress, risks, and limitations.
  • Hands-on experience with large language models and generative AI frameworks, including Microsoft Foundry and/or Azure OpenAI endpoints, as well as LLM orchestration tools such as LangChain, LangGraph, or equivalent R-based tools such as ellmer.
  • Proficiency in R and/or Python, with comfort working across both languages in a production environment.
  • Strong foundation in statistical modeling, including GLMs, gradient boosting, and other techniques used for risk assessment and pricing.
  • Experience building and deploying models in cloud-based production environments (Azure preferred).
  • Demonstrated ability to communicate complex technical findings clearly to business stakeholders (written, verbal, and data visualization).
  • A strong appreciation for contributing and maintaining well-written documentation. You value version control (git).
  • Strong problem-solving orientation with a bias toward action and delivery.
  • Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa.

Preferred Qualifications:

  • Experience in property and casualty insurance, specialty lines, or a related financial services domain with familiarity with underwriting workflows and pricing concepts.
  • Familiarity with actuarial methods, GLM-based pricing, or experience collaborating with actuarial teams.
  • Experience with Posit Connect, Posit Workbench, Shiny, or Quarto for production deployment and reporting.
  • Knowledge of web scraping, API integration, or unstructured data extraction pipelines.
  • Demonstrated ability to mentor data scientists and elevate team technical capabilities.
  • Experience setting up or contributing to MLOps practices, including model versioning, code reproducibility management, and CI/CD for analytical pipelines.

Pay Range

$120,000.00 - $160,000.00 Annual

The pay range provided above is made in good faith and based on our lowest and highest annual salary or hourly rate paid for the role and takes into account years of experience required, geography, and/or budget for the role.

Teammate Benefits & Total Well-Being

We go beyond standard benefits, focusing on the total well-being of our teammates, including:

  • Health Benefits: Medical/Rx, Dental, Vision, Life Insurance, Disability Insurance
  • Financial Benefits: ESPP; 401k; Student Loan Assistance; Tuition Reimbursement
  • Mental Health & Wellness: Free Mental Health &Enhanced Advocacy Services
  • Beyond Benefits: Paid Time Off, Holidays, Preferred Partner Discounts and more.

Not reflective of all benefits. Enrollment waiting periods or eligibility criteria may apply to certain benefits. Benefit details and offerings may vary for subsidiary entities or in specific geographic locations.

The Power To Be Yourself

As an Equal Opportunity Employer, we are committed to fostering an inclusive environment comprised of people from all backgrounds, with a variety of experiences and perspectives, guided by our Diversity, Inclusion & Belonging (DIB) motto, "The Power to Be Yourself".