Sr. Scientist
OR · On-site +1
Utilize tools like R, R Shiny, or Python libraries (e.g., Matplotlib, Seaborn) to build intuitive ... Proficiency in programming languages such as Python or R, SQL, and data visualization tools.
OR · On-site +1
Utilize tools like R, R Shiny, or Python libraries (e.g., Matplotlib, Seaborn) to build intuitive ... Proficiency in programming languages such as Python or R, SQL, and data visualization tools.
OR · On-site +1
Utilize tools like R, R Shiny, or Python libraries (e.g., Matplotlib, Seaborn) to build intuitive ... Proficiency in programming languages such as Python or R, SQL, and data visualization tools.
$54.50 - $72/hr
Overview LMI is seeking a skilled Developer to join our team and contribute to developing ... Familiarity with R and Shiny for statistical computing and interactive applications is a plus
$54.50 - $72/hr
Overview LMI is seeking a skilled Developer to join our team and contribute to developing ... Familiarity with R and Shiny for statistical computing and interactive applications is a plus
$66K - $86K/yr
Overview LMI is seeking a skilled Developer to join our team and contribute to developing ... Familiarity with R and Shiny for statistical computing and interactive applications is a plus
$66K - $86K/yr
Overview LMI is seeking a skilled Developer to join our team and contribute to developing ... Familiarity with R and Shiny for statistical computing and interactive applications is a plus
$14.74 - $21.95
10% of jobs
$25.82 is the 25th percentile. Wages below this are outliers.
$21.95 - $29.16
29% of jobs
$29.16 - $36.37
4% of jobs
$36.37 - $43.58
4% of jobs
$43.58 - $50.78
0% of jobs
$50.78 - $57.99
2% of jobs
The median wage is $58.47 / hr.
$57.99 - $65.20
16% of jobs
$69.77 is the 75th percentile. Wages above this are outliers.
$65.20 - $72.41
16% of jobs
$72.41 - $79.62
12% of jobs
$79.62 - $86.83
3% of jobs
$86.83 - $94.04
4% of jobs
$14
$52
$94
R Shiny Developers often encounter challenges such as optimizing app performance with large datasets, ensuring cross-browser compatibility, and balancing feature-rich functionality with ease of use. Teams typically support developers through code reviews, collaborative problem-solving sessions, and access to best practice documentation or established Shiny frameworks. Employers may also encourage ongoing learning through training or attendance at data science meetups, ensuring developers stay up to date with the latest tools and techniques. Addressing these challenges effectively helps deliver robust, high-impact applications that empower data-driven decisions.
An R Shiny Developer is responsible for building interactive web applications using R and the Shiny framework. They design, develop, and optimize dashboards or tools to visualize and analyze data dynamically. This role often requires expertise in R programming, data manipulation, UI/UX design, and deploying Shiny apps. R Shiny Developers commonly work with data scientists and analysts to translate data insights into user-friendly applications.
To thrive as an R Shiny Developer, you need strong programming skills in R and Shiny, a solid understanding of data analysis, and a relevant degree in computer science, statistics, or a similar field. Familiarity with version control systems like Git, experience deploying Shiny apps on cloud platforms, and knowledge of UI/UX best practices are highly valued. Excellent problem-solving abilities, clear communication, and a collaborative mindset set top candidates apart. These skills are essential for building effective, user-friendly data applications that meet business and user requirements in a team environment.

7.7
Based on 35 frontline employees who took The Breakroom Quiz
51st of 105 rated laboratories
Sr. Scientist Real-World Evidence - Chronic Kidney Disease and Rare Disease
Location: San Carlos, CA, Austin, TX, or Remote, USA
Sr. Scientist -CKD and rare disease
Job Summary
Natera is seeking an innovative and driven bioinformatics scientist to lead and execute cutting-
edge "real-world evidence" (RWE) analyses and predictive modeling across key areas of Organ
Health, Rare Disease, and Women's Health. This unique role requires a blend of expertise in
bioinformatics, strong project management skills, and a dedication to impactful data
visualization to advance our understanding and application of genomics in a real-world clinical
setting.Key Responsibilities
RWE and Bioinformatics Analysis: Lead large-scale genomics data analysis,
specifically in Chronic Kidney Disease (CKD), to extract actionable insights. Apply
advanced bioinformatics tools and techniques to interpret genomic data within the
context of RWE studies.
Predictive Analytics & Modeling: Develop and implement robust predictive models to
forecast clinical trends and outcomes using RWE and genomics data. Utilize machine
learning and statistical modeling to uncover patterns that inform clinical decision-making
and strategic business development.
Data Visualization and Communication: Create and implement innovative data
visualization strategies to effectively communicate complex genomic analysis results.
Utilize tools like R, R Shiny, or Python libraries (e.g., Matplotlib, Seaborn) to build
intuitive, interactive, and impactful visual representations.
Project Leadership: Own and manage genomics projects from initial concept through to
final delivery, ensuring all initiatives are completed efficiently (on time and within budget)
while maintaining the highest quality and scientific standards.
Cross-Functional Partnership: Collaborate closely with Sales, R&D, Data Science,
Business Development, Medical Affairs, Product Management, and Engineering to
seamlessly integrate genomics data into broader research and development initiatives.
Data Stewardship: Facilitate the integration of genomics data with diverse data types
(e.g., clinical and demographic) to enrich analyses. Oversee the management of large
datasets, ensuring data integrity, security, and confidentiality.
Reporting and Publication: Prepare detailed reports and manuscripts for publication.
Present complex genomics data and analyses in a clear, concise manner to varied
audiences, including technical experts and non-technical stakeholders.
Innovation and Development: Maintain current knowledge of the latest developments
in genomics and bioinformatics. Propose and develop novel methods and technologies
for advanced data analysis and predictive modeling.
Stakeholder Engagement: Act as a key liaison between the technical team and non-
technical partners, engaging with stakeholders to define project goals, communicate
progress, and discuss findings that drive the business forward.
Qualifications
Ph.D. in Bioinformatics, Computational Biology, Genetics, or a closely related field.
A minimum of 5 years of post-doctoral or professional experience in a relevant field.
Proven expertise in bioinformatics, with a strong emphasis on genomics data analysis.
Extensive experience managing and analyzing large-scale genomic and healthcare
datasets.
Demonstrated expertise in human genomics, including familiarity with inherited
disorders, genomic alterations, molecular mechanisms, and disease biology.
Expert knowledge of bioinformatics tools for data processing, including mapping, variant
calling, CNV analysis, and core statistical methods.
Solid understanding of real-world data (RWD) sources such as electronic health records,
claims data, patient registries, or health surveys. Ability to interpret clinical endpoints,
understand patient cohorts, and successfully collaborate with clinical stakeholders.
Proficiency in predictive analytics, machine learning, and statistical modeling is required.
Excellent project management skills with a proven record of leading successful, complex
projects.
Proficiency in programming languages such as Python or R, SQL, and data visualization
tools.
Exceptional written and verbal communication skills for both technical and non-technical
audiences.
Proven experience collaborating effectively with diverse cross-functional teams,
including clinicians, scientists, biostatisticians, regulatory affairs, and external
stakeholders.
Experience managing one or more direct or indirect reports is a plus.
Knowledge of translational medicine and/or early discovery in the biotech or
pharmaceutical industry is a plus.
Personal Attributes
Ability to produce high-quality written documentation for varying audiences.
Demonstrated capacity to work independently while effectively managing multiple
objectives and timelines.
A desire to work in a fast-paced environment with the potential for high impact as part of
a small, dynamic team.
Additional expertise in germline genetics, particularly in relation to organ health and
women's health, is a significant advantage.