Data Scientist / Machine Learning (TS SCI + Poly is Required)

Our Mission Statement

At Aperio Global, we bring together experts in cybersecurity, AI, data analytics, and cloud technologies to solve complex national security challenges. We focus on work where our expertise creates the greatest impact.

Our team includes technologists, Intelligence Community veterans, and security professionals who believe the best solutions come from collaboration, accountability, and technical excellence. From cyber operations and AI platforms to cloud-native software and emerging technologies, our work speaks for itself.

Come Solve With Us

We offer competitive pay, comprehensive benefits, retirement savings with company match, generous paid time off, and professional development. We invest in our people because great missions require great teams.

U.S. Citizenship is required for this position due to federal government contract and security clearance requirements.

This position requires and ACTIVE and CURRENT TS SCI with a POLYGRAPH to be considered. 

Aperio Global  is seeking a Data Scientist to develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

Overview: 

Level 1

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

Level 2

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

Security Clearance Requirements:

This position requires all candidates to be U.S. Citizens and possess an active TS/SCI Security Clearance with a Polygraph.

Qualifications:

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 and developing 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.

Level 2: 

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.

Anticipated Salary Range; 

LEVEL 1     150-170  

LEVEL 2    170-190

The salary range for this role represents Aperio’s good-faith estimate of compensation at the time of posting. Placement within the range is based on multiple factors, including but not limited to an individual’s qualifications, relevant experience, education, certifications, technical skills, contract labor categories and/or rates, work location, market conditions, and business needs.

Benefits

At Aperio Global, we understand the value of investing in our most important asset-our employees. That's why we have crafted a comprehensive benefits package designed to help you make the best decision for yourself, your family and your lifestyle. For additional details, contact our talent acquisition team.

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA) with 100% employer match up to 6%
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Short Term & Long Term Disability
• Professional Development
• (and much more)

Aperio Global is an equal opportunity employer. We are committed to building an inclusive workforce where all employees and applicants are treated with respect and fairness. Employment decisions are based solely on qualifications, merit, and business needs - never on race, color, religion, sex, national origin, age, disability, genetic information, military or veteran status, pregnancy/childbirth, sexual orientation, gender identity, marital status, ethnicity, or any other characteristic protected by applicable federal, state, or local law.