Technical Lead - Biological Systems Modeling Analytics

Battelle•Columbus, OH

11d•Hybrid

About The Position

Battelle delivers when others can’t. We conduct research and development, manage national laboratories, design and manufacture products and deliver critical services for our clients—whether they are a multi-national corporation, a small start-up or a government agency. We recognize and appreciate the value and contributions of individuals from a wide range of backgrounds and experiences and welcome all qualified individuals to apply. Job Summary We are currently seeking a Technical Lead - Biological Systems Modeling Analytics for a hybrid work arrangement. This position is located in Columbus, OH. Battelle's Health Analytics supports government, academic and private industry clients in the areas of public health, healthcare, national defense, environmental, transportation, and energy. In this role you will fulfill data analysis needs for complex and unusual problems, and you will oversee junior staff on small tasks and work closely with other senior technical staff. In this role you will be focused on (i) developing technical solutions, (ii) implementing, evaluating, and improving state‑of‑the‑art models and data analysis pipelines, (iii) developing reports or presentations to report findings to project leaders and clients, and (iv) providing technical expertise to support business development activities.

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, bioinformatics, or related domain
Expertise in one or more of the following: Statistical modeling and machine learning
Differential equation-based modeling (ODE/PDE/stochastic systems)
Bayesian methods and probabilistic modeling
Experience working with large-scale, high-dimensional biological or chemical datasets
Strong programming skills (e.g., Python, R, MATLAB or similar)
Proven ability to communicate complex technical concepts to technical and non-technical audiences
Ability to obtain and maintain Secret clearance

Nice To Haves

Demonstrated success contributing to the capture and execution of federal research and development programs, including development of technical approaches, solution concepts, white papers, proposals, and client-facing presentations.
Experience serving as a technical lead, principal investigator, task lead, or subject matter expert on multidisciplinary scientific programs.
Knowledge of the federal health, biodefense, environmental health, and life-sciences research landscape, including agencies such as NIH, FDA, CDC, BARDA, DoD, EPA, DARPA, and ARPA-H.
Proven ability to translate complex scientific, computational, and modeling concepts into clear and concise written, visual, and verbal communications for both technical and non-technical audiences.
Experience supporting business development activities, including identifying opportunities, shaping technical solutions, evaluating teaming approaches, assessing technical risks, and contributing to competitive proposal efforts.
Demonstrated ability to collaborate effectively across disciplines, including biologists, toxicologists, statisticians, software engineers, and domain subject matter experts.
Experience mentoring junior scientists and supporting growth of technical capabilities within a research team.
Strong scientific curiosity and commitment to continuous learning in emerging areas such as AI/ML, systems biology, computational modeling, and advanced analytics.
Excellent written and verbal communication skills, including experience presenting technical work to clients, partners, program managers, and senior leadership.
Ability to engage with stakeholders possessing varying levels of scientific and technical expertise and clearly communicate the mission impact of scientific solutions.
Ability to work independently while also contributing effectively to small, fast-paced, multidisciplinary research

Responsibilities

Develop and implement computational toxicology models, including PBPK/PBTK and quantitative adverse outcome pathway (qAOP) frameworks
Design and apply machine learning and statistical models to classify, cluster, and predict toxicity of chemical compounds using large-scale datasets (e.g., Tox21, bioactivity data)
Build multi-scale models using differential equations (ODE/PDE), stochastic processes, and Bayesian methods
Apply advanced analytics techniques, including multivariate statistical analysis, dimensionality reduction, and probabilistic inference
Develop algorithms for pattern recognition, classification, and predictive modeling across biological and chemical datasets
Collaborate with multidisciplinary teams including biologists, toxicologists, statisticians, and software engineers
Translate complex scientific outputs into clear, actionable insights and technical deliverables
Support proposal development and technical solutioning for federal health and environmental programs (e.g., CDC, NIH, FDA, EPA)
Mentor junior staff and contribute to development of scientific and analytic capabilities across the team