Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUI with Security Clearance

Constellation Technologies, Inc; Maryland; On-site; USD 120,000 - 220,000; Full time

Benefits offered by this job

Healthcare

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

Education Reimbursement

Job summary

Constellation Technologies, Inc. seeks a data/ML specialist with TS/SCI clearance and US citizenship to work on large datasets and analytic workflows. You will apply mathematics, statistics and programming to model, explore, and interpret data from sensitive agency sources.

The role requires expertise in Python, ML and data tools, plus strong communication to non-technical stakeholders. Security clearance is mandatory, with compliance to federal requirements.

Qualifications

• Degree in Mathematics, CS or related field with advanced math coursework.
• Experience in ML, data science, data mining, statistics, and AI.
• Ability to code in Python and at least one mid-level language like C.

Responsibilities

• Devise strategies to extract meaning from large datasets.
• Communicate conclusions using math, statistics and CS concepts.
• Develop methods to characterize and explore data with agency-specific constraints.
• Translate mission needs into technical requirements and solutions.
• Explain complex technical info to non-technical audiences.

Skills

Python

C

Machine Learning

Data Analysis

Statistical Methods

Data Mining

Education

Bachelor's degree in Mathematics or Computer Science or related field

Tools

Jupyter

Spark

Job description

Job Overview

Big Data, dataflows, Artificial Intelligence / Machine Learning (AI/ML) familiarity, Analytics in GME, Jupyter notebooks, and Spark. Due to federal contract requirements, United States citizenship and an active TS/SCI security clearance and polygraph are required for the position.

Compensation

$120,000 - $220,000 a year The pay range for this job, with multi-levels, is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

Required Qualifications

• Must be a US Citizen
• Must have TS/SCI clearance w/ active polygraph
• This position is open to multiple levels of years of experience; two (02) years within the last five (05) years must be directly related to the job you are applying for:
• Level 04 requires a minimum seventeen (17) years of experience w/ Degree
• Level 03 requires a minimum twelve (12) years of experience w/ Degree
• Level 02 requires a minimum five (05) years of experience w/ Degree
• Degree in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g., physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e., behavioral, social, and life) may be considered if it includes a concentration of coursework (typically 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).
• College-level Algebra or other math courses intended to meet a basic college level requirement, or upper-level math courses designated as elementary or basic do not count.
• Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g. C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity.
• Employ some combination (2 or more) of the following 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).

Key Responsibilities

• 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.
• Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent to Agency data holdings.
• 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 the constantly shifting Agency collection, processing, storage and analytic capabilities and limitations.

Nice-to-Have Qualifications

• Fully Cleared polygraph is preferred
• Knowledge of working with Big Data, dataflows, Machine Learning/Artificial Intelligence familiarity.
• Analytics in GME, Jupyter notebooks, and Spark.

Benefits Package

• Affordable healthcare options with 80% employer paid premium PLUS a company-funded HSA
• Comprehensive Dental insurance
• Vision with 80% employer paid premium
• Employer paid Life insurance 100%
• Employer paid Short-term and Long-term disability 100%
• Annual training, continued education, and professional memberships reimbursement
• Unlimited access to Red Hat Enterprise Linux and AWS training and accreditation
• Annual reimbursement for technology i.e. phones, computers, printers, etc.
• 401(k) with company match up to 5% with 100% immediate vesting (after 90 days of employment)

Environment & Perks

• Professional development investment and paid time off for training
• Contract and work locations in Maryland, Virginia, Colorado, Texas, Utah, Florida and Hawaii.
• Team building events throughout the year such as Destination