Data Scientist, Level 2

WOOD Consulting Services • Ft. Meade, MD

1d • Onsite

About The Position

A Data Scientist transforms complex datasets into clear, meaningful insights—building and testing machine learning, statistical, and graph‑based algorithms, creating data when it doesn’t exist, and delivering crisp visualizations that guide smarter decisions. They collaborate with subject‑matter experts to automate analysis and push prototype analytics into real production workflows. Step into a role where your models drive real‑world impact—your ideas will shape missions, and your growth will have no ceiling. This position requires all candidates to be U.S. Citizens and possess an active TS/SCI Security Clearance with a Polygraph.

Requirements

• Requires a Bachelor's degree in a relevant discipline (e.g., statistics, mathematics, operations research, engineering, or computer science) from an accredited college or university, eight (8) years of relevant experience analyzing datasets and developing analytics, and five (5) years of relevant experience programming with data analysis software such as R, Python, SAS, or MATLAB.
• A Master's degree in relevant discipline may be substituted for two (2) years of relevant experience reducing the requirement to six (6) years of relevant experience analyzing datasets and developing analytics, and three (3) years of relevant experience programming with data analysis software such as R, Python, SAS, or MATLAB.
• A PhD in relevant discipline may be substituted for four (4) years relevant experience reducing the requirement to four (4) years of relevant experience analyzing datasets and developing analytics, and one (1) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
• In lieu of a Bachelor’s Degree, an additional four (4) years of relevant experience may be substituted for a total of twelve (12) years of relevant experience analyzing datasets and developing analytics, and nine (9) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
• U.S. Citizens
• Possess an active TS/SCI Security Clearance with a Polygraph.

Responsibilities

• Produce data visualizations that provide insight into dataset structure and meaning.
• Collaborate with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs).
• Incorporate SME input into feature vectors suitable for analytic development and testing.
• Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
• Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics.
• Develop statistical tests to make data-driven recommendations and decisions.
• Develop experiments to collect data or models to simulate data when required data are unavailable.
• Develop feature vectors for input into machine learning algorithms.
• Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
• Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
• Evaluate individual analytic efforts and make recommendations in the analytic development process.
• Recommend solutions that can scale to large datasets.
• Collaborate with software engineers, cloud developers, and appropriate stakeholders to develop production analytics.
• Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation.

Benefits

• Comprehensive medical, dental, and vision plans.
• 401(k) with company match.
• Generous PTO policy including vacation, sick leave, and holidays.
• Opportunities for training, certifications, and career advancement.
• Flexible work schedules and remote work options.
• Employee assistance programs, wellness initiatives, and gym membership discounts.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level