Senior Data Scientist at Aptima Inc

Fairborn, Ohio, United States -

Full Time

Start Date

Immediate

Expiry Date

08 Oct, 26

Salary

150000.0

Posted On

10 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI/ML Modeling, Python, SQL, LangChain, LangGraph, Statistical Analysis, Experimental Design, Agentic Workflow Design, Data Pipeline Development, Multimodal Analysis, Human-Centered AI, Technical Leadership, Stakeholder Engagement, Quantitative Modeling, Pandas, NumPy

Industry

Defense and Space Manufacturing

Description

Description Who We Are Aptima is a technological leader in the national security industry. Our mission is to drive the future of national security by engineering scalable solutions that fuse technological innovation with human potential to transform how individuals and teams train, develop, and perform in mission-critical environments. Our culture is rooted in our core values, which have evolved over time and our employees have embraced: Integrity, Ingenuity, Excellence, Respect, Engagement, Teamwork. At our core, Aptima researches, develops, and innovates within an area that engineering firms largely ignore, the human component. To impact the world in meaningful ways, you must bring those innovations to light, and that is precisely what we do. How You Will Make An Impact The Senior Data Scientist leads data driven problem solving, including design and technical execution, by applying modern AI/ML techniques in dynamic systems that drive our tech enabled solutions for our Department of War (DoW) customers. This role combines expertise in translating problem requirements and model selection with applied AI system design and project leadership, serving as a technical lead on multidisciplinary programs and coordinating the work of AI engineers and researchers. The position emphasizes end-to-end data modeling ownership, hands on interaction with stakeholders, and translation of mission needs into operationally effective capabilities, while contributing to proposals, customer engagements, and internal technical excellence. Key Responsibilities Lead the design of ML/AI models, interaction workflows, and recommendation system’s designed for skill selection or staff profiles. Understand the science that can inform requirements addressing trust, explainability, complexity, and characteristics of modern ML solutions. Serve as technical lead or task lead on AI and human–AI system development efforts, coordinating work across AI engineers and researchers. Translate mission needs and human performance objectives into system requirements, technical architectures, and evaluation plans. Review and guide system implementations to ensure usability, explainability, and operational suitability. Design and execute experiments and statistical studies to evaluate traditional AI/ML, as well as generative AI and agentic systems. Design, develop, and oversee analytic pipelines and performance metrics to operationalize complex behavioral and organizational constructs using real-world data. Translate quantitative results into clear, actionable insights for technical teams, behavioral scientists, and government stakeholders, bridging theory, data, and system implementation. Lead technical contributions to proposals, system designs, and customer deliverables. Present technical work internally and at relevant external forums to include conferences, customer briefings, and other venues. Mentor junior staff and promote best practices in human-centered AI system development. Contribute to internal initiatives for AI system development and evaluation. Requirements We are open to candidates willing to work in Aptima's Dayton office, Orlando office, or in the DC area MS or PhD in data science, computer science, applied mathematics, physics, or related STEM field. Demonstrated expertise in the AI/ML applications and experiments, spanning stakeholder engagement, requirements scoping, and development of technical solutions. Strong quantitative modeling and statistical analysis background, including experimental design, supervised and unsupervised learning, and multimodal analysis. Hands-on experience with AI agent development and evaluation, including agentic workflow design, tool integration, and output benchmarking using frameworks such as LangChain and LangGraph. Proficiency in Python for data analysis, modeling, simulation, visualization, and development of reproducible analytic workflows; experienced with tools such as pandas, NumPy, Matplotlib/Plotly, and Jupyter-based environments. Proficiency in SQL for data querying, transformation, and pipeline development across relational and cloud-based data platforms. Experience developing custom metrics, indices, and analytic pipelines to operationalize complex behavioral, organizational, or team constructs using real-world, imperfect data. Experience designing and executing human-subject experiments and analyzing performance data. Experience leading technical tasks or serving as technical lead or PI on government-funded programs. Strong written and verbal communication skills, including proposal and customer-facing technical work. Proven ability to translate quantitative results into clear, actionable insights for technical teams, behavioral scientists, and non-technical stakeholders, serving as a bridge between disciplines. Ability to manage and coordinate multidisciplinary technical teams. Ability to obtain and maintain a security clearance; familiarity with DoW research environments preferred. Willingness to travel as needed. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or any other status protected by applicable national, federal, state or local law.

Responsibilities

Lead the design and execution of AI/ML models and agentic systems to solve complex problems for Department of War customers. Coordinate multidisciplinary teams of researchers and engineers to translate mission needs into operational technical architectures.