Data Scientist

MANTECH•Charlottesville, VA

6d•$85,300 - $141,400•Hybrid

About The Position

MANTECH International Corporation is seeking a motivated Data Scientist to join their team. This role involves leading and supporting the full lifecycle development and deployment of analytical solutions, acting as a trusted advisor to client partners. Data scientists at MANTECH leverage advanced analytical methods to transform ambiguous business challenges into high-impact, production-ready solutions supported by robust data engineering practices. The position is hybrid, requiring 1-2 days onsite per week, and is located in Raleigh, NC, Washington DC, or Charlottesville, VA.

Requirements

3+ years of experience as a Data Scientist with a Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or the social or natural sciences.
High proficiency in Python and/or R, including libraries for data analysis and modeling.
Experience developing machine learning models and employing model validation best practices.
Strong SQL experience to facilitate deep dives and analysis of complex datasets.
Working knowledge of version control (Git) for source code.
Initiative and willingness to “hit the ground running” on new projects; unafraid to work independently.
Passion and curiosity for exploring data to understand the business context and connect technical work to real-world impact.
Excitement to continually learn new tools and techniques.
Humility and eagerness to collaborate with other data scientists, data engineers, engagement and project managers, and clients.
Interest in developing and contributing to instruction for data science and AI training courses.
Ability to communicate complex technical findings to a variety of audiences, including those with limited data science experience.

Nice To Haves

Exceptional comfort with ambiguity and a proven ability to define and drive projects from vague concepts to concrete outcomes.
Strong consultative and communication skills to represent the team effectively to clients.
Ability to work autonomously in fully remote, flexible client environments.
Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields.
Experience applying advanced statistical concepts and data science workflows to real-world data, including out-of-sample validation for various model types, sampling considerations, bias detection, handling missing or outlying data, and robust exploratory analysis.
Understanding of the data analytics lifecycle (e.g., CRISP-DM).

Responsibilities

Lead and Contribute to Data Science Projects: Dive deeply into complex and often nebulous requirements and draw from your expertise to develop production-ready models and analytics products for our clients. Clients’ needs can require a broad set of analytics skills including but not limited to time series forecasting, natural language processing (NLP), classification/regression modeling, and optimization.
Design Solutions within Client Environments: Adapt project work to the client’s tooling and environment requirements. This will oftentimes require quickly learning new systems and tools to be able to deliver solutions that will work well within a client’s ecosystem.
Consult with Clients to Solve Problems: Engage in critical requirements gathering and data “sleuthing” to connect business use cases with the right analytics techniques to provide real-world impact. You will often work directly with clients to define and solve problems that lack clear initial definitions and will regularly communicate your solutions directly to stakeholders.
Develop, Lead, and Support Analytics Training Courses: Develop and/or teach bespoke data science, AI, or related material designed specifically for Elder Research clients. This can include support for active courses through lecture, mentoring, and grading.
Collaborate and Communicate: Work with internal teams and external client stakeholders to effectively communicate technical findings, maintain strong relationships, and ensure delivery aligns with overall objectives.