Sr. Scientist

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.

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.