Subject Matter Expert - Epidemiology & Clinical Data Science

The EMMES Corporation•Rockville, MD

5h•Remote

About The Position

Subject Matter Expert - Epidemiology & Clinical Data Science US Remote This position supports "Essex, an Emmes Company". Essex is a biomedical informatics and health information technology-focused consultancy founded in 2009 and headquartered in Rockville, MD. The Essex team comprises experts with extensive experience in strategically developing and managing complex health and biomedical information programs for clients in the Federal Government, research academia, and private sectors. Emmes Group: Building a better future for us all. Emmes Group is transforming the future of clinical research, bringing the promise of new medical discovery closer within reach for patients. Emmes Group was founded as Emmes more than 47 years ago, becoming one of the primary clinical research providers to the US government before expanding into public-private partnerships and commercial biopharma. Emmes has built industry leading capabilities in cell and gene therapy, vaccines and infectious diseases, ophthalmology, rare diseases, and neuroscience. We believe the work we do will have a direct impact on patients’ lives and act accordingly. We strive to build a collaborative culture at the intersection of being a performance and people driven company. We’re looking for talented professionals eager to help advance clinical research as we work to embed innovation into the fabric of our company. If you share our motivations and passion in research, come join us! Primary Purpose Essex seeks a Subject Matter Expert (SME) in Epidemiology & Clinical Data Science to help provide senior clinical and scientific leadership for projects involving clinical research, real‑world evidence (RWE), and data‑driven health research. The SME advises on study design, statistical methodology, and interpretation of complex health data; guides the standardization and integration of clinical and trial data into common data models; and ensures deliverables meet regulatory, quality, and client requirements. The SME collaborates across multidisciplinary teams (clinical, data science, engineering, and program leadership) to translate scientific findings into actionable insights and scalable, researcher‑facing products.

Requirements

Doctorate‑level or medical degree-level clinical/scientific expertise with demonstrated success leading complex studies and producing peer‑reviewed outputs.
Demonstrated data science and quantitative analysis experience applied to clinical, public health, or biomedical research questions.
Strong epidemiology and biostatistics foundation; ability to select and justify methods, interpret results, and explain limitations and bias considerations to diverse audiences.
Hands‑on analytic capability with common tools (e.g., R and SQL; familiarity with statistical packages such as SPSS).
Experience with clinical research execution and evidence generation, including clinical trials and/or real-world evidence workflows.
Excellent written and verbal communication skills, including scientific writing, data storytelling, and executive‑level briefings.
Ability to work independently under general direction; strong judgment, prioritization, and stakeholder management in fast‑moving environments.
Doctorate‑level degree (e.g., MD/PhD) with twelve (12) years of progressively responsible experience in the individual’s field of specialization.
Proven history of achievement in a scientific/clinical setting (academic, public health, and/or industry), including publication record and collaborative research experience.
Eligibility to work in the United States and to obtain/maintain a government Public Trust (or similar) clearance, if required by the contract.

Nice To Haves

Experience collaborating with cross‑functional AI/ML teams on healthcare use cases (e.g., clinical decision support, monitoring, risk prediction).
Good Clinical Practice (GCP) training and familiarity with regulatory expectations for clinical research documentation.
Experience translating heterogeneous clinical data into standardized representations (e.g., common data models, controlled terminologies).
Experience in occupational/environmental health and/or chronic disease research domains.
Demonstrated mentoring and training experience for students and health professionals; multilingual communication skills are a plus.

Responsibilities

Serve as the clinical/scientific SME and task lead for complex clinical research and data science activities; provide expert guidance to align work with program objectives, business strategy, and public health impact.
Engage with stakeholders (scientific investigators, client leadership, and cross‑functional teams) to synthesize needs, communicate findings, and deliver executive‑level briefings and presentations.
Provide clinical and translational perspective to data science and AI/ML teams to ensure analytic outputs and models are medically meaningful, appropriately validated, and clearly communicated.
Participate in all phases of project execution (planning, requirements, analysis, design, integration, documentation, implementation, and operations), with emphasis on high‑impact scientific and methodological decisions.
Advise on development and adoption of clinical data standards and data dictionaries for new clinical areas; support governance processes and facilitate data sharing agreements and data use terms with data owners/partners.
Coordinate, curate, and interpret clinical trial and observational data; transform heterogeneous data to a common standard and support publication‑quality analytics and reproducible reporting.
Ensure delivery within established timelines, budgets, and resource constraints, and in alignment with applicable regulatory, quality, privacy, and safety requirements.
Lead or contribute to quality assurance (QA) reviews of scientific deliverables; identify gaps, recommend corrective actions, and ensure traceability from requirements to implementation.
Mentor and coach analysts, researchers, and junior staff in epidemiology/biostatistics methods, research rigor, and scientific writing; support knowledge transfer and training activities.