About
Data Scientist, Junior to Mid-Level
Location
US-MD-Ft. Meade
Job ID
WOOD-0063
# Positions
1
Experience (Years)
4
Category
Software Engineering
Overview
Data Scientist, Junior to Mid-Level woodcons.com Location:
Full-Time Shift
Ft. Meade, Maryland, USA Job Type:
Days Telework
None Salary Range:
Education
$140,000 to $195,000 ** Salary ranges are based on minimum education and years of experience and may increase based on education and/or experience. Overview:
We are looking for talented and driven Data Scientists to join our team on a government contract. The successful candidate will be responsible for developing advanced machine learning, data mining, statistical, and graph-based algorithms to analyze and interpret complex datasets. Key responsibilities include rototyping and evaluating multiple algorithms to select the best-performing model; building models or designing experiments to generate data when training datasets are unavailable; creating reports and visualizations to summarize datasets and provide actionable insights; collaborating with subject matter experts to automate manual data analysis processes; implementing prototype algorithms within production frameworks for seamless integration into analyst workflows. This role offers a unique opportunity to contribute to critical government projects and drive data-driven decision-making. Application Process:
Interested candidates should submit their resume detailing their qualifications and experience. Security Clearance Requirements: This position requires all candidates to be
U.S. Citizens
and
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.
Qualifications
Junior Data Scientist: Requires a Bachelor's degree in a relevant discipline (e.g., statistics, mathematics, operations research, and engineering or computer science) from an accredited college or university, and four (4) years of experience analyzing datasets and developing analytics and two (2) year of 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 analyzing datasets anddeveloping analytics, and one (1) year of relevant 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 eight (8) years of relevant experience analyzing datasets and developing analytics, and two (2) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
Mid-Level Data Scientist: 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.
About WOOD
Fringe Benefits: Health Insurance:
Comprehensive Medical, Dental, And Vision Plans. Retirement Plan
401(k) with company match. Paid Time Off:
Generous PTO policy including vacation, sick leave, and holidays. Professional Development:
Opportunities For Training, Certifications, And Career Advancement. Work-Life Balance
Flexible work schedules and remote work options. Wellness Programs:
Employee assistance programs, wellness initiatives, and gym membership discounts. Why Join Us? Impactful Work:
Contribute to critical government projects that make a difference. Career Growth:
Take advantage of professional development opportunities and career advancement. Supportive Environment:
Work in a collaborative and flexible environment that values work-life balance. Competitive Compensation:
Enjoy a competitive salary and comprehensive benefits package.
Nice-to-have skills
- Machine Learning
- Data Mining
- Statistics
- SQL
- Python
- R
- SAS
- Matlab
- Maryland, United States
Work experience
- Data Engineer
- Fullstack
- Machine Learning
Languages
