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Data Science Major Jobs in Oregon (NOW HIRING)

Represent Natera as a senior scientific authority at major oncology congresses, ensuring all field data-handling methods maintain absolute alignment with HIPAA, CAP/CLIA, PHI data protocols, FDA ...

... Data Science, or related field. * 3+ years of hands-on experience in AI/ML model development and deployment. * Strong programming skills in Python and experience with major ML/AI frameworks ...

OR

$122K - $161K/yr

... as a Data Scientist or ML Engineer * Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform ...

OR · On-site

... commercial data solutions, data science). Trinity is investing in expanding our Analytics ... Bachelor's degree (or advanced degree a plus) with high academic achievement; major in health ...

Showing results 41-60

Data Science Major information

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

To thrive as a Data Science Major, you need a solid understanding of mathematics, statistics, and programming languages such as Python or R, typically backed by coursework or a related degree. Familiarity with data analysis tools, machine learning libraries, and platforms like SQL, TensorFlow, or Jupyter Notebook is also important. Critical thinking, effective communication, and problem-solving skills help you interpret data insights and collaborate on projects. These competencies enable you to extract meaningful information from data, drive decision-making, and succeed in a data-driven environment.

What is a data science major?

A Data Science major is an academic program that focuses on teaching students how to collect, analyze, and interpret large sets of data to solve real-world problems. It combines coursework in statistics, computer science, mathematics, and domain-specific knowledge to prepare graduates for roles in various industries such as technology, healthcare, finance, and more. Students learn programming languages like Python or R, machine learning techniques, and data visualization skills. The major often includes hands-on projects and internships to provide practical experience in analyzing and extracting insights from data.

What types of projects or problems do data science majors typically work on during internships or entry-level roles?

Data Science majors in internships or entry-level positions often collaborate on projects involving data cleaning, exploratory data analysis, and building predictive models. They might work with real-world datasets to identify trends, automate reporting, or support business decision-making with data-driven insights. These roles typically require teamwork with software engineers, business analysts, and domain experts, offering valuable opportunities to apply classroom knowledge to practical challenges and to develop skills in popular tools like Python, R, and SQL.

What is the difference between Data Science Major vs Data Analyst?

AspectData Science MajorData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldsDegree in Statistics, Mathematics, or related fields
Work EnvironmentResearch, development, and complex data modelingData interpretation, reporting, and visualization
Industry UsageTech companies, finance, healthcare, academiaBusiness, marketing, finance, healthcare
Common Search/ComparisonData Science Major vs Data Analyst

While both roles involve working with data, a Data Science Major typically prepares individuals for complex data modeling, machine learning, and research tasks. In contrast, a Data Analyst focuses on interpreting data, creating reports, and visualizations to support business decisions. The roles often overlap, but the Data Science Major emphasizes advanced analytics and programming skills, whereas Data Analysts concentrate on data interpretation and communication.

What are popular job titles related to Data Science Major jobs in Oregon? For Data Science Major jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Data Science Major jobs in Oregon look for? The top searched job categories for Data Science Major jobs in Oregon are:
What cities in Oregon are hiring for Data Science Major jobs? Cities in Oregon with the most Data Science Major job openings:
Infographic showing various Data Science Major job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Director, Field Translational Science - Oncology

Natera

OR

Full-time

Re-posted 28 days ago


Natera rating

7.6

Company rating: 7.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

60th of 120 rated laboratories


Job description

Director, Field Translational Science - Oncology Position Summary

Natera is shifting disease management worldwide through unprecedented molecular innovation. As the Director of Field Translational Science, you will build, scale, and lead a specialized team of field-facing translational scientists within our Oncology Business Unit. This high-autonomy leadership role is designed for a strategic builder who can run a sophisticated regional team while serving as the executive authority for advanced Natera tests - including, but not limited to, cell-free DNA (cfDNA) and minimal residual disease (MRD) assays - and their associated data analysis frameworks across elite academic medical centers.

This position requires up to 50-70% regional travel to engage with institutional leadership and audit high-priority research partnerships. You will eliminate the standard boundaries between field data generation and internal pipeline design. Distinct from traditional, education-focused Medical Affairs teams (MSLs), your organization owns the structural integrity, statistical validation, and scientific output of investigator-led data collaborations.

Primary Responsibilities
  • Team Leadership & Scale: Hire, develop, and manage a premier field organization of translational scientists, establishing clear performance metrics tied to regional data velocity, scientific rigor, and publication quality.
  • Strategic Data Architecture: Author and execute the regional data engagement strategy, guiding how field scientists partner with oncologists, pathologists, and biometricians to unlock complex ctDNA and real-world datasets; holds the institutional/enterprise escalation line for the direct day-to-day communication line with the clinicians.
  • Regional Operations & Systems Governance: Oversee the secure regional tracking architecture and data ingestion pipelines that individual Field Translational Scientists operate within; ensure absolute data compliance, system integrity, and streamlined data flow from investigator sites into internal analysis platforms. 
  • Cross-Functional Governance: Command the interface between field operations and internal Oncology Translational Medicine & Scientific Communications, Medical Affairs, Life Cycle,  R&D and Product Development leadership, translating field-derived real-world evidence into high-impact pipeline recommendations.
  • Investigator-Led Portfolio Management: In partnership with MSLs, oversee the lifecycle of all regional investigator-initiated trials (IITs) and institutional registries, ensuring team members enable investigators to maximize the utility of Natera's proprietary analytical tools and data visualization platforms to achieve statistical robustness and prompt manuscript generation.
  • Institutional Network Expansion: Secure, scale, and manage institutional data-sharing models, biobanking governance, and EMR data-integration initiatives with core comprehensive cancer networks.
  • Scientific Advocacy & Compliance: Represent Natera as a senior scientific authority at major oncology congresses, ensuring all field data-handling methods maintain absolute alignment with HIPAA, CAP/CLIA, PHI data protocols, FDA regulations, and PhRMA codes of interaction.
Qualifications
  • Required Education: PhD or MD in Cancer Biology, Genomics, Bioinformatics, or a related complex molecular science discipline.
  • Required Experience: 6+ years of total experience within basic or translational oncology research, including a minimum of 2+ years of explicit people management experience leading high-performing scientific or clinical teams within the diagnostics,  biotechnology or pharmaceutical sectors.
  • Domain Mastery: Exceptional command of cancer biology and genetics, liquid biopsy modalities and clinical utilities, next-generation sequencing (NGS) and ctDNA workflows and data interpretation, and statistical methods.
  • Data-Centric Track Record: Documented success managing complex genomic datasets, institutional electronic medical record (EMR) integrations, or complex clinical data registries.
  • Leadership Style: Proven ability to manage teams through high ambiguity, prioritizing structured logic and rapid, high-judgment decision-making over consensus-driven delays.
  • Operational Mobility: Ability and willingness to travel domestically up to 50-70% to support team execution, site audits, and principal investigator collaborations.

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