Overview In this role you will lead and execute advanced modeling and analytics in biological systems, guiding junior staff and collaborating with cross-disciplinary experts. You will develop and evaluate state-of-the-art toxicology models and data pipelines, translate complex results into actionable insights, and support business development with technical solutions. The position sits within Battelle's Health Analytics, serving government, academia, and private sector clients. You will work hybrid in Columbus, OH, tackling high-impact problems at scale.
Compensation / Benefits- hybrid work arrangement
- flexible, compressed schedule (every other Friday off)
- 60% in-office / 40% remote
- medical/dental/vision coverage with wellness incentives
- retirement plan with company match (401(k) up to 5% + match)
- tuition assistance
Responsibilities- Develop and implement computational toxicology models (PBPK/PBTK, qAOP)
- Design and apply ML/statistical models to predict chemical toxicity using large-scale datasets (e.g., Tox21)
- Build multi-scale models (ODE/PDE, stochastic, Bayesian)
- Apply advanced analytics: multivariate analysis, dimensionality reduction, probabilistic inference
- Develop algorithms for pattern recognition, classification, and predictive modeling in biological/chemical data
- Collaborate with biologists, toxicologists, statisticians, and software engineers
- Translate scientific outputs into clear, actionable technical deliverables
- Support proposal development and technical solutioning for federal programs (CDC, NIH, FDA, EPA)
- Mentor junior staff and contribute to scientific/analytic capability development
Key requirements- Ph.D. in computational biology, bioinformatics, physics, chemistry, applied mathematics, or related field
- 8+ years of experience in computational modeling, data science, or quantitative biology
- Demonstrated experience in computational toxicology or bioinformatics
- Expertise in statistical modeling and machine learning
- ODE/PDE/stochastic modeling experience
- Bayesian methods and probabilistic modeling
- Experience with large-scale high-dimensional datasets
- Strong programming skills (Python, R, MATLAB)
- Proven ability to communicate complex concepts to technical and non-technical audiences
- Ability to obtain and maintain Secret clearance
- clear communication
- mentorship
- cross-functional collaboration
- Statistical modeling
- Machine learning
- Differential equation-based modeling (ODE/PDE)
