Head of Statistics

Overview

Headwater Science (formerly NoviSci) is a data science and methods company specializing in principled, reproducible evidence generation for complex clinical and regulatory challenges. With deep expertise in comparative effectiveness, causal inference, healthcare utilization and expenditure research, and regulatory-grade analytical software, Headwater Science provides the methodological foundation that delivers reproducible analytic pipelines, novel epidemiologic and statistical methods, and regulatory-grade software validated to hold up under the most demanding scrutiny. The company works with life sciences organizations as a long-term scientific partner. Headwater Science is a Highlander Health company. Learn more at headwaterscience.com .

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 Headwater’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

What We Offer You

Hybrid work — 3 days/week in office to collaborate with the team

Comprehensive health, dental, and vision for you and your family

401(k) with company match

Generous PTO and company holidays

Paid parental leave

If you are ready to be part of a team where your work truly matters—where your expertise is valued, your growth is supported, and your contributions help shape the future of healthcare—Headwater Science is the place for you. We're building something meaningful together, and we'd love for you to be a part of it.

Headwater Science is an equal opportunity employer and seeks candidates from diverse backgrounds and abilities.