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Quantitative Science Jobs (NOW HIRING)

DIR DIVISION OPERATIONS

Tampa, FL · On-site

$140 - $230/hr

The Population Science Division and the Physical and Quantitative Science (PQS) Division at Moffitt Cancer Center advance cancer research through complementary, data‐driven, and interdisciplinary ...

Required : • PhD or equivalent experience in ML, computer science, or a quantitative science. • Deep familiarity with large models and a passion for understanding how they work. • Fluency in ...

The Population Science Division and the Physical and Quantitative Science (PQS) Division at Moffitt Cancer Center advance cancer research through complementary, datadriven, and interdisciplinary ...

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How much do quantitative science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for quantitative science in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What is a quantitative science?

A Quantitative Science job involves applying mathematical, statistical, and computational techniques to analyze data and solve complex problems. Professionals in this field work across industries such as finance, healthcare, technology, and research, using models and algorithms to derive insights and make data-driven decisions. They often work with large datasets, employing machine learning, statistical modeling, and data visualization to interpret results. Strong analytical skills and proficiency in programming languages like Python, R, or SQL are commonly required.

What are some typical projects or tasks a quantitative science professional might work on?

A Quantitative Science professional often works on projects such as developing predictive models, designing experiments or surveys, analyzing large datasets, and reporting findings to stakeholders. You might collaborate closely with data engineers, business analysts, and subject matter experts to translate complex data insights into actionable recommendations. It's common to use statistical software and programming languages daily, and project work can range from short-term analyses to long-term research initiatives. The role offers a stimulating mix of independent analytical work and cross-functional teamwork, with opportunities to contribute to strategic decisions within an organization.

What are the key skills and qualifications needed to thrive in the quantitative science position, and why are they important?

To thrive in a Quantitative Science role, you need a strong background in mathematics, statistics, and data analysis, typically supported by an advanced degree in a quantitative discipline. Familiarity with programming languages such as Python or R, statistical modeling software, and experience with data visualization tools are highly valued. Problem-solving, critical thinking, and the ability to communicate complex findings clearly are important soft skills for success. These abilities are essential for accurately interpreting data, informing business or research decisions, and collaborating effectively with multidisciplinary teams.

What does a quantitative science do?

A professional in quantitative science analyzes numerical data to solve complex problems, often using statistical, mathematical, and computational methods. They work in fields like finance, research, or technology, utilizing tools such as programming languages and data analysis software to develop models and inform decision-making.
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What states have the most Quantitative Science jobs?

States with the most job openings for Quantitative Science jobs include:

Infographic showing various Quantitative Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 74% Physical, 4% Hybrid, and 22% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Vice President, Quantitative Sciences & Development

SK Life Science

Paramus, NJ • On-site

Other

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


Job description

Vice President, Quantitative Sciences & Development

The Vice President, Quantitative Sciences & Development provides strategic, scientific, and operational leadership for the company's Clinical Pharmacology, Pharmacometrics, Toxicology, DMPK, Biostatistics, Statistical Programming, and Clinical Data Management functions across all phases of drug development.

This executive is responsible for developing and overseeing execution of integrated quantitative strategies that support efficient translation from non-clinical development, clinical development, regulatory submissions, and evidence generation while ensuring delivery of high-quality, inspection-ready clinical data and statistical analyses. The VP serves as a key member of the Clinical Leadership Team and partners closely with Clinical Development, Clinical Operations, Regulatory Affairs, Medical Affairs, Pharmacovigilance, Quality Assurance, and external CROs to advance the company's portfolio.

Responsibilities

Develop and implement the company's Clinical Pharmacology, Biometrics and Data Sciences strategy aligned with corporate development objectives.

Serve as a key member of the Clinical Leadership Team.

Build organizational capabilities to support a growing clinical pipeline.

Lead organizational planning, budgeting, resource allocation, and vendor strategy.

Represent Clinical Pharmacology, Data Management, and Biometrics in governance committees and executive reviews.

Clinical Pharmacology & Toxicology

Provide strategic oversight for:

  • First-in-human (FIH) study design
  • SAD/MAD studies
  • Food-effect and drug-drug interaction (DDI) studies
  • QT/QTc and organ impairment studies
  • Population PK, PBPK modeling, exposure-response analyses, dose optimization, and model-informed drug development (MIDD)
  • Nonclinical toxicology strategy, including general, reproductive, developmental, genotoxicity, and carcinogenicity studies, as applicable
  • Guide clinical pharmacology and toxicology strategy across all phases of development.
  • Review and approve PK/PD and toxicology protocols, analysis plans, study reports, and regulatory submissions.
  • Interpret nonclinical safety data to support first-in-human studies, dose selection, and benefit-risk assessments.
  • Ensure compliance with FDA, EMA, PMDA, and ICH guidance and represent the function in regulatory interactions and cross-functional governance.
Biostatistics

Provide strategic oversight for all biostatistical activities supporting clinical development.

Responsibilities include:

  • Develop statistical strategy across the clinical development portfolio.
  • Oversee study design and statistical methodology.
  • Review and approve:
    • Statistical Analysis Plans (SAPs)
    • Protocol statistical sections
    • Interim analyses
    • Adaptive design methodologies
    • Integrated summaries
    • TLFs (Tables, Listings, and Figures)
  • Guide sample size estimation, endpoint selection, multiplicity strategies, estimands, and innovative trial designs.
  • Support Data Monitoring Committees (DMCs), Independent Review Committees (IRCs), and interim decision-making.
  • Provide statistical leadership for:
    • NDA/BLA submissions
    • FDA Type B/C meetings
    • EMA Scientific Advice
    • PMDA interactions
  • Ensure statistical integrity and regulatory compliance across all studies.
Statistical Programming

Provide executive oversight of statistical programming activities including:

  • SDTM and ADaM dataset development
  • TLF (Tables, Listings, and Figures) generation
  • CDISC implementation
  • SAS and R programming standards
  • Submission-ready datasets
  • Define.xml preparation
  • Regulatory submission programming
  • Automation and programming innovation
  • Validation and quality control processes

Establish efficient programming standards that ensure timely database analyses and global submission readiness.

Clinical Data Management
  • Provide executive oversight of all Clinical Data Management activities.
  • Ensure high-quality, inspection-ready clinical databases.
  • Oversee:
    • IWRS (Interactive Web Response System)/IRT (Interactive Response Technology) design
    • Database design
    • CRF/eCRF development
    • Data review plans
    • Data cleaning
    • Medical coding
    • Database lock
    • Data quality metrics
  • Establish enterprise data standards including:
    • CDISC SDTM
    • CDASH
    • Controlled Terminology
  • Ensure timely delivery of clean data for interim analyses and regulatory submissions.
  • Lead implementation of innovative technologies including:
    • Risk-based data review
    • Centralized monitoring
    • AI-assisted data review
    • Electronic Clinical Outcome Assessments (eCOA)
    • Wearable device integration
    • Decentralized clinical trial data capture
Cross-Functional Collaboration

Partner closely with:

  • Clinical Development
  • Clinical Operations
  • Regulatory Affairs
  • Medical Affairs
  • Safety/Pharmacovigilance
  • Medical Writing
  • Clinical Supply
  • Quality Assurance
  • Commercial
  • Health Economics & Outcomes Research (HEOR)
Regulatory Leadership
  • Provide clinical pharmacology leadership for regulatory interactions.
  • Lead preparation of:
    • Clinical Pharmacology Summary
    • Module 2.7 documents
    • Module 5 components
    • NDA/BLA/MAA submissions
  • Support FDA Type A/B/C meetings, End-of-Phase meetings, and Advisory Committees.
  • Respond to global regulatory information requests.
Vendor Management
  • Select, oversee, and evaluate CROs and specialty vendors.
  • Establish KPIs and performance metrics.
  • Manage budgets and contracts.
  • Ensure vendor compliance with GCP and company quality standards.
Quality & Compliance
  • Ensure compliance with:
    • ICH GCP
    • FDA regulations
    • EMA guidance
    • 21 CFR Part 11
    • GCDMP
    • Company SOPs
  • Maintain inspection readiness.
  • Support regulatory inspections and audits.
People Leadership
  • Build, mentor, and lead high-performing Clinical Pharmacology, Biometrics and Data Management teams.
  • Recruit and retain top scientific and operational talent.
  • Foster a culture of innovation, collaboration, accountability, and continuous improvement.
  • Develop succession plans and leadership capabilities.
Qualifications

PhD, PharmD, MD, or equivalent advanced degree in:

  • Clinical Pharmacology
  • Pharmaceutical Sciences
  • Pharmacokinetics
  • Biomedical Sciences
  • Biostatistics
  • Medicine
  • Related scientific discipline

Work Experience:

  • 15+ years of progressive pharmaceutical