At Target RWE, our mission is driven by a deep commitment to people, whether it’s the patients we serve, the partners we collaborate with, or the dedicated team members who power our work. As a purpose-driven organization, we leverage real-world data to advance clinical research and inform better healthcare decisions. We foster a collaborative environment where every voice is heard, every idea has an impact, and every contribution helps improve lives. If you're seeking a place where your work truly matters, join us to advance science.

Overview

We are seeking a Principal to join Target RWE’s Quantitative Sciences (QS) organization. In this role, you will help shape how we design, execute, and communicate real-world clinical studies using Target’s data.

This is a highly cross-functional and client-facing role. You will bring strong analytical and scientific expertise, paired with the ability to apply the right level of methodological rigor for the question at hand, balancing credibility, practicality, and clarity. You will work closely with internal teams and external partners to ensure analyses are scientifically sound, clearly communicated, and aligned with real-world use cases.

You will serve as a key representative of Target’s scientific capabilities, engaging directly with pharmaceutical and biotech partners, supporting client discussions, and helping translate complex analytical approaches into clear, actionable insights.

What You’ll Do

Applied Methodology and Study Design

You will ensure that Target’s analyses are scientifically rigorous, practical, and aligned with real-world use.

• Guide the design of observational studies using real-world data, including retrospective and prospective analyses
• Apply statistical and epidemiologic methods in a practical, fit-for-purpose way
• Develop and review study protocols and statistical analysis plans
• Ensure analyses are reproducible, interpretable, and aligned with regulatory and scientific expectations
• Partner with internal teams to translate research questions into practical analytic approaches

Client-Facing Scientific Leadership

You will serve as a key scientific voice in client and partner interactions.

• Participate in and lead client meetings to explain study design, methodology, and results
• Translate complex analytical concepts into clear, accessible language for diverse audiences
• Support business development efforts by helping communicate Target’s scientific approach and data value
• Represent Target in external settings, including conferences, scientific collaborations, and partner discussions
• Build trust with clients by providing thoughtful, pragmatic, and credible scientific guidance

Cross-Functional Collaboration

You will connect data, analytics, and business needs across the organization.

• Partner closely with Product, Engineering, Medical Science, Clinical Operations, and Commercial teams
• Help shape analytic strategies that align with both scientific goals and customer needs
• Provide guidance to the Quantitative Sciences team on study design and interpretation
• Mentor team members on balancing methodological rigor with practical execution
• Contribute to internal best practices for scalable, high-quality evidence generation

What You’ll Bring

• PhD or MS in biostatistics, epidemiology, health economics, data science, or a related field
• 10+ years of experience working with real-world data (EMR, claims, registry, or clinical trial data)
• Strong foundation in observational study design and applied statistical methods; experience with real-world pragmatic clinical trial designs is a plus
• Demonstrated ability to apply methods pragmatically, selecting the right approach for the problem
• Willingness to engage directly with data and analyses as needed, with working knowledge of R and/or SQL to support exploratory work, validation, and collaboration with analytic teams
• Experience working directly with clients or external partners in life sciences or healthcare
• Excellent communication and presentation skills, with the ability to explain complex concepts clearly
• Comfortable operating in client-facing settings, including meetings, presentations, and scientific discussions
• Strong collaboration skills across technical and non-technical teams

What we offer you

• Hybrid work — 3 days/week in our brand-new office!
• Comprehensive health, dental, and vision for you and your family
• 401(k) with company match
• Generous PTO and company holidays
• Paid parental leave 

Head of Statistics

Overview

NoviSci is a data science organization with a dual mission: 1) developing best-in-class software to support the generation of RWE and 2) executing high-impact, tech-enabled scientific consulting and research.

We are seeking a Head of Statistics who will own the statistical functional area- serving as the center of excellence for statistical rigor, methodology, methods standardization, and professional development across the organization. This is a hands-on leadership role for a methodologist who wants to build: building a team, building methods, and building the statistical backbone of real-world evidence software.

You will work shoulder-to-shoulder with the Head of Science, Product, Engineering, and Statistical Software Development, translating advanced causal inference and epidemiologic methods into robust software requirements, clear APIs, and scalable analytical tools. If you enjoy making hard statistical problems accessible, and care deeply about scientific credibility, this role is for you.

Statistical leadership & strategy

• In collaboration with the Head of Statistical Software Development, define and execute the statistical methods roadmap across products and services
• Serve as the functional center of excellence for statistical rigor, methods standardization, code reproducibility, and adoption of advanced causal inference and epidemiologic methods for real-world data
• Lead the development and implementation of causal inference, advanced epidemiologic, and statistical methods for real-world evidence generation, ensuring scientific rigor, transparency, and reproducibility
• Guide the design of longitudinal and observational study workflows, including uncertainty quantification and sensitivity analyses
• Represent NoviSci’s statistical perspective with external partners, clients, collaborators, and at scientific venues as a subject-matter expert

Product partnership (requirements, architecture, APIs)

• Collaborate with Product, Statistical Software Development, and Engineering to:
• Translate statistical and methodological needs into product requirements and roadmaps
• Advise on high-level system and architecture decisions
• Co-design API specifications (inputs/outputs, parameterization, defaults, error handling, diagnostics) and review PRDs/tech specs for statistical fidelity
• Provide reference implementations and simulation harnesses used as ground truth for verification; help design CI checks and validation datasets
• Establish documentation standards for methods notes, assumptions, and user-facing guidance

High-value scientific delivery

• Serve as a senior statistical contributor on select research pods, providing high-level expertise, validating analyses, and pioneering new methods
• Architect statistical designs for causal estimation of complex interventions under confounding, missingness, and dependent censoring
• Develop and review statistical analysis plans (SAPs), code, figures, and outputs for validity, reproducibility, and regulatory readiness
• Support quality and compliance processes in partnership with the Head of Operations, ensuring analysis validation, audit trails, and reproducibility standards are met

Thought partnership for clients

• Act as a senior statistical advisor to client teams (HEOR, Med Affairs, Epi); help mature their internal evidence pipelines and governance
• Evaluate statistical methodology choices for complex study designs, including distributed and federated analyses
• Guide clients on methods choices for regulatory submissions and HTA assessments

Team building & mentorship

• Serve as functional manager for all statisticians: hire, mentor, train, and conduct performance reviews
• Develop and enforce standards and SOPs for statistical analysis, code reproducibility, and methods adoption across the statistics group
• Foster a rigorous, supportive, and learning-oriented culture within the statistics functional group
• Uplevel engineers and PMs on statistical, advanced epidemiologic methods, including causal inference; uplevel statisticians on software craft (versioning, testing, CI/CD, profiling)

Required background

• PhD (or equivalent) in Biostatistics, Statistics, Epidemiology, or a related quantitative field
• 4+ years of post-doctoral experience spanning causal inference, advanced epidemiologic methods, statistical software development, and real-world data (claims, EHR, registries)
• Demonstrated track record of leading complex observational studies through publication and/or regulatory use
• Deep, hands-on expertise in causal inference and advanced epidemiologic methods for real-world data, including:
• Target trial emulation
• IP weighted estimators for confounding, missingness, and censoring
• Clone-censor-weighted estimation of dynamic treatment regimens
• Marginal structural models (MSMs), IPTW, and IPCW
• Uncertainty quantification and sensitivity analysis
• Proven ability to translate statistical and methodological requirements into product requirements, architecture trade-offs, and API designs in close partnership with engineering
• Strong experience with R, including package development, testing, and performance profiling
• Experience collaborating closely with software engineers in a production or near-production environment
• Evidence of thought leadership (publications, invited talks, open-source contributions, or methods papers)

Nice-to-have background

• Experience designing statistical APIs or platforms used by external customers
• Familiarity with regulatory expectations for RWE (e.g., FDA, EMA guidance on real-world evidence)
• Experience with CMS/Medicaid data governance and multi-source linkage/tokenization
• Prior experience managing or mentoring senior statisticians or data scientists
• Experience working in a fast-paced, product-driven or startup environment
• Comfort with protocol/report generators and figure/table QA pipelines (e.g., Quarto/R Markdown)
• Fluency with AI/ML coding tools (e.g., GitHub Copilot, Cursor) and comfort incorporating them into statistical programming and reproducible research workflows

If you’re excited to advance the science of real-world evidence in an environment where statistical rigor directly shapes both client impact and software innovation, NoviSci is the place for you. We’re building something important together, and we’d love for you to be a part of it.

What We Offer You

• Comprehensive health, dental, and vision coverage for you and your family
• 401(k) with company match
• Generous PTO and company holidays
• Paid parental leave
• Hybrid role: Located in Research Triangle Park, North Carolina

At Target RWE, our mission is driven by a deep commitment to people, whether it’s the patients we serve, the partners we collaborate with, or the dedicated team members who power our work. As a purpose-driven organization, we leverage real-world data to advance clinical research and inform better healthcare decisions. We foster a collaborative environment where every voice is heard, every idea has an impact, and every contribution helps improve lives. If you're seeking a place where your work truly matters, join us to advance science.

Overview

In this role, you will be a foundational member of Target RWE’s Quantitative Sciences (QS) organization, helping to establish Target as a leader in rigorous, reproducible, and regulatory-grade evidence generation. You will serve as a scientific owner of Target’s data, developing deep expertise in its structure, quality, and applications while helping to build scalable data validation, curation, and analytic processes that ensure reliability and usability.

Working closely with cross-functional partners in Product, Engineering, Clinical Operations, and Medical Science, you will design and execute analyses that demonstrate the value of Target’s data, support customers across life sciences, regulatory, and academic settings, and build scalable, standardized analytic approaches for real-world evidence generation.

What You’ll Do

1. Data Ownership and Quality 

• You will establish Target’s data as a trusted, validated scientific asset.
• Ensure Target’s data are accurate, complete, and fit for regulatory and scientific use by building systems and practices that establish trust in data integrity and readiness for analysis.
• Develop deep expertise in Target’s data, understanding its structure, provenance, strengths, and limitations.
• Design and implement validation frameworks, data quality checks, and “fitness-for-use” assessments.
• Create and maintain data dictionaries and documentation that promote transparency and reproducibility.

2. Analytical excellence 

• You will apply advanced analytic methods and scientific rigor to generate reliable, reproducible, and regulatory-grade real-world evidence from Target’s data assets.
  • Support the design and execution of retrospective and prospective studies using Target’s data assets.
  • Develop statistical analysis plans and analytic code for descriptive, comparative, and predictive analyses.
  • Design and implement scalable, reusable analytic frameworks and modular code structures that support consistent execution across therapeutic areas and data products.
  • Apply best practices in methodology, version control, code review, and documentation to ensure reproducibility.
  • Translate complex results into clear visualizations and insights for scientific, regulatory, and client audiences.
  • Contribute to publications, abstracts, and collaborations that advance Target’s scientific reputation and influence.

3. Cross functional partnership

• You will work cross-functionally to connect data, science, and strategy, ensuring Target’s evidence generation aligns with customer needs and business goals.
• Partner closely with Commercial, Medical Science, Product, Data Insights, Engineering, and Clinical Operations teams to align on data strategy and analytic priorities.
• Serve as the internal “voice of the customer,” anticipating how clients, regulators, and researchers will use Target’s data.
• Participate in client and partner meetings to demonstrate the validity and value of Target’s data products.
• Leverage your deep knowledge of Target’s data assets to guide internal teams and external partners, anticipating analytical and operational challenges and helping to shape data use strategies.
• Translate analytic findings and data characteristics into clear, client-facing materials that demonstrate Target’s data quality, representativeness, and scientific utility.

What You’ll Bring

• Advanced degree (MS or PhD) in biostatistics, epidemiology, health economics, bioinformatics, data science, or a related quantitative field. 
• 5-10+ years of experience working with real-world data (e.g., EMR, claims, registry, or clinical trial data).
• Strong programming expertise in R, and experience with reproducible analytic frameworks.
• Proven expertise in data quality assessment, validation, and curation workflows.
• Demonstrated ability to build and maintain reproducible coding practices and scalable analytic processes that enable efficiency, transparency, and consistency across studies.
• Strong communication, presentation and collaboration skills with cross-functional technical and scientific teams.
• Demonstrated ability to translate data insights into actionable scientific or business recommendations.

What we offer you

• Hybrid work — 3 days/week in our brand-new office!
• Comprehensive health, dental, and vision for you and your family
• 401(k) with company match
• Generous PTO and company holidays
• Paid parental leave