Head of Statistics

Reposted 16 Hours Ago
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Triangle Trailer Park, Township of Jacksonville, NC, USA
In-Office
Senior level
Biotech
The Role
The Head of Statistics will lead statistical methodologies, team building, product requirements translation, and ensure scientific rigor in RWE generation at NoviSci.
Summary Generated by Built In
Head of StatisticsOverview

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

Skills Required

  • PhD in Biostatistics, Statistics, Epidemiology, or a related field
  • 4+ years of post-doctoral experience
  • Hands-on expertise in causal inference and advanced epidemiologic methods
  • Strong experience with R, including package development
  • Experience collaborating with software engineers
Am I A Good Fit?
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The Company
HQ: Durham, NC
136 Employees
Year Founded: 2015

What We Do

As the industry’s best-in-class, complete real world evidence (RWE) solution, Target RWE is a distinctly collaborative enterprise that unifies real world data (RWD) sets and advanced RWE analytics in an integrated community, shifting the paradigm in healthcare for how decisions are made to improve lives. Target RWE sources unique, connected data sets across multiple therapeutic areas representing granular data from diverse patients in academic and community settings. Our rigorous, interactive, and advanced RWE analytics extract deep insights from RWD to answer important questions in healthcare. Target RWE brings together the brightest minds in healthcare through an unmatched community of key opinion leaders, patients, and healthcare stakeholders in a collaborative and dynamic model. Learn more about Target RWE: www.targetrwe.com

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