Data Scientist and/or Systems Analyst

MIT Lincoln Laboratory•Lexington, MA

10d•$145,200 - $220,000•Onsite

About The Position

The Bioanalytics Systems & Technologies Group develops analytic and AI/ML solutions using large and expanding biological datasets to address national security needs. Its work includes software architectures and systems, bioinformatics tools, and AI algorithms supporting biomedical, health, chemical and biological defense, biosecurity, public and global health, and warfighter performance. The Data Scientist and/or Systems Analyst will provide technical leadership across programs and contribute hands-on throughout the AI/ML lifecycle, from generative modeling and data strategy through rigorous evaluation. The role also involves shaping methods and tools that generalize across data modalities and mission applications. As Technical Staff, the employee will serve as a principal investigator for projects, lead teams, define research plans, and provide technical oversight. The role is collaborative and interdisciplinary. The employee will help teams understand mission needs, prototype capabilities and solutions, and recommend technology capabilities, requirements, architectures, and pipelines for U.S. government needs. The position connects data, model development, and capability evaluation into coherent, reusable technical approaches. The position is onsite only.

Requirements

Ph.D. in Applied Mathematics, Bioinformatics, Biomedical Engineering, Computational Biology, Computer Science, Data Science, Physics, Statistics, or a related scientific field; a master's degree with 7+ years of directly related experience may be considered instead.
Strong analytical and systems-thinking skills, including the ability to design approaches that generalize across data types and use cases.
Ability to understand big-picture motivations, operational constraints, and stakeholder needs while also addressing underlying technical details.
Demonstrated experience applying AI/ML techniques to answer research questions or solve practical technical problems.
Demonstrated ability to collaborate and lead small to medium teams of diverse backgrounds and skillsets to execute a technical vision and deliver program success.
Demonstrated scientific writing skills and ability to present technical materials clearly to technical experts and non-technical stakeholders.
Ability to obtain and maintain a Secret-level DoD security clearance.
U.S. citizenship is required.
Must undergo a pre-employment background investigation.

Nice To Haves

Additional experience beyond the Ph.D.
Experience developing solutions in cloud environments such as AWS and working with data lakes or warehouses.
Experience with data curation, annotation, integration, harmonization, and scalable ML data pipelines.
Experience with simulation environments, digital twins, or synthetic data generation for training and validating algorithms.
Experience with systems analysis using modeling and simulation to understand trade-offs in complex systems.
Experience designing or applying evaluation frameworks and metrics for AI model/system performance and trustworthiness.
Experience with health or healthcare-related data and analytics, including EHR data structures and clinical data standards.
Hands-on experience with generative modeling techniques and/or LLM-based tool development, such as RAG architectures, prompt engineering, or model evaluation.

Responsibilities

Analyze user needs and operational constraints.
Recommend technology capabilities, requirements, architectures, and data/ML pipelines.
Design, prototype, and evaluate analytics and modeling solutions.
Design and conduct technology verification and validation, including testing software and systems with users or subject-matter experts in realistic settings.
Collaborate with multidisciplinary teams, including scientists, engineers, and analysts, to translate technical work into mission-relevant capabilities.
Communicate technical findings and recommendations clearly to technical and non-technical stakeholders.
Serve as a principal investigator for projects, lead teams, define research plans, and provide technical oversight.