Data Scientist

Marquee Defense; Fort Meade (MD); On-site; USD 120,000 - 170,000; Full time

Job summary

Marquee Defense seeks a data science professional to analyze large datasets, build models, and deliver actionable insights for mission-critical programs at Fort Meade. Proficiency in Python, JupyterLab, ML, and visualization is required.

Ability to communicate complex results to non-technical stakeholders is essential; TS/SCI with Polygraph clearance is mandatory. Experience with REST APIs, data management, and software engineering is a plus.

Qualifications

• Bachelor’s degree with substantial relevant experience.
• Experience designing and interpreting large datasets.
• Proficiency in Python and data science toolchain.

Responsibilities

• Devise strategies for extracting meaning and value from large datasets.
• Communicate principled conclusions using math, statistics, CS, and domain knowledge.
• Develop methods for characterizing, exploring, and assessing datasets.

Skills

Python

JupyterLab

REST API

Plotly

Bokeh

Matplotlib

Machine Learning

Statistical Analysis

Data Management

Data Modeling

Software Engineering

Multidisciplinary

Education

Bachelor's Degree with 10 years of relevant experience

Associate's Degree with 12 years of relevant experience

Certificate in Data Science

Tools

JupyterLab

REST API

Visualization Software

Job description

Fort Meade or National Business Park area

Job Type:

Full time in-person

Clearance:

Top Secret/SCI with Polygraph

Description

Employ some combination (2 or more) of the following skill areas:

Foundations: (Mathematical, Computational, Statistical)

Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility)

Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)

Devise strategies for extracting meaning and value from large datasets

Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge

Develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure

Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data

Effectively communicate complex technical information to non-technical audiences

Make informed recommendations regarding competing technical solutions by maintaining awareness of technical tradeoffs between processing, storage, and analytic requirements

Work Experience

NOTE: Military Multiplier: Relevant military experience is credited as 1.25X years experience!

Bachelor’s Degree with 10 years of relevant experience

Associates degree with 12 years of relevant experience

Specialty Experience

None required

Programming (skill in at least one high-level language (e.g. Python)),

JupyterLab

REST API network calls

Visualization software (Plotly, Bokeh, Matplotlib)

Designing/implementing machine learning

Advanced analytical algorithms

Statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application oflinear models)

Data management (e.g. data cleaning and transformation)

Data modeling and assessment

Software engineering

Experience in more than one area is strongly preferred

Education

A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university

Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering)

Physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence)

Marquee Defense is an equal opportunity employer (EEO)

All applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.