Senior Clinical Developer/SME (R+Clinical)

Job Title: Senior Clinical Developer/SME (R+Clinical)

Location: Anywhere in East Coast

What This Role Requires
In this role, you will be a key contributor to MResult's mission of empowering our clients with data-driven insights and innovative digital solutions. Each day brings exciting challenges and growth opportunities. Here is what you will do:
Roles and Responsibilities:
Architect PK Data Pipelines: Design and maintain robust, reproducible R-based workflows for processing raw clinical data into analysis-ready datasets (e.g., PC, PP domains) for Non-Compartmental Analysis (NCA) and Population PK modelling.
Tool & Package Development: Lead the development of internal R packages for PK/PD analysis, ensuring code quality through unit testing, documentation (Roxygen2), and version control (Git).
Interactive Analytics: Build and deploy sophisticated R Shiny dashboards for clinical teams to perform real-time data exploration, dose-escalation monitoring, and safety-efficacy visualization.
Cross-Functional Strategy: Collaborate with Pharmacometricians to optimize data transfer from R to modelling software (e.g., NONMEM, Monolix) and back for post-processing.

Key Skills to Succeed in This Role:
Advanced R Mastery: 8+ years of deep R experience, including the tidyverse, data.table, and object-oriented programming (S3/S4/R6).

Pharmacometrics Toolkit: Expert-level knowledge of PK-specific R libraries such as mrgsolve, rxode2, PKNCA, or nca.
Statistical Standards: Proficiency in CDISC standards (SDTM and ADaM), specifically regarding PC (Pharmacokinetic Concentrations) and PP (Pharmacokinetic Parameters) domains.
Modeling Integration: Extensive experience preparing data for NONMEM, NLME, or Phoenix WinNonlin.
Reproducible Research: Mastery of R Markdown or Quarto for automated, high-fidelity clinical reporting.

Clinical & Domain Expertise:
PK/PD Knowledge: Deep understanding of pharmacokinetic concepts (e.g., $C_{max}$, $AUC$, clearance, volume of distribution) and how they are derived from clinical trial data.

Good to Have:
Regulatory Submissions: Oversee the generation of Tables, Listings, and Figures (TLFs) and Clinical Study Reports (CSR) sections. Ensure all deliverables meet FDA/EMA/PMDA standards.
Technical Leadership: Mentor junior programmers and data scientists in R best practices, software development life cycle (SDLC), and efficient PK data handling.
DevOps & Version Control: Advanced Git workflows (branching, PR reviews) and experience with CI/CD pipelines for R package validation.
Regulatory Compliance: Comprehensive understanding of GXP, ICH-GCP, and 21 CFR Part 11 guidelines for computer system validation.
Trial Design Awareness: Experience with First-in-Human (FIH), MAD/SAD, and DDI (Drug-Drug Interaction) study designs.