Job BriefData scientist, AI/ML, RAG
Job DescriptionYour effort and expertise are crucial to the success and execution of this impactful mission. This opportunity supports a team of Data Scientists, Cryptologic Computer Scientists, Cryptanalytic Computer Scientists, Cryptologic Cyber Planners, Intrusion Analysts, Protocol Analysts, Signals Analysts and Reverse Engineers, responsible for improving, protecting, and defending our Nation's Security.
Job Description:- We are seeking a Data Scientist who is an established AI expert with demonstrable experience in designing and implementing sophisticated AI/ML and data science solutions across various domains within the customer environment. You will help to establish an authoritative role in a customer-prioritized and highly visible AI system that will be of critical use. You will need to to have experience designing and building customized capabilities to enable Retrieval Augmented Generation (RAG) for multiple enterprise data sets, agentic AI systems to automate and orchestrate decision-making actions across specialized AI resources, and Docker-based microservices, user-facing GUIs, and cloud-hosted services (Kubernetes architecture) hosted on AWS/Azure/Google service platforms. attribution.
The Level 4 Data Scientist shall possess the following capabilities:- 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).
- Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge.
- Ability to use 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 feature and limitations inherent in Government 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.
Qualifications:- Bachelor's Degree with 15 years of relevant experience.
- Associate's degree with 17 years of experience may be considered for individuals with in-depth experience that is clearly related to the position.
- Bachelor'sDegree must be in 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), 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, 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). College-level requirement, or upper-level math courses designated as elementary or basic do not count.
- Broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
- Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.
- Experience with designing and building:
- Customized capabilities to enable Retrieval Augmented Generation (RAG) for multiple enterprise data sets.
- Agentic AI systems to automate and orchestrate decision-making actions across specialized AI resources.
- Docker-based microservices, user facing GUIs, and Cloud-hosted services (Kubernetes architecture) hosted on AWS/Azure/Google service platforms.
- Deep knowledge and experience in AI solutions and an ability to assess, evaluate, and implement the correct ML models for specific purposes and optimized performance.
- Experience generating, evaluating, training, and optimizing Machine Learning models (i.e. LLMs) for use in low-memory, low-resourced edge device environments.
- Proficient in the development and application of advanced analytical algorithms, advanced statistical techniques, statistical outlier detection, data clustering, and graph-based analysis.
- Capable of using data processing and data automation techniques for ETL operations and injection into ELK systems and databases.
- Familiar with graph theory, graph algorithms (i.e. community detection), techniques to design and generate large-scale graphs (nodes and links) from diverse data sources, and techniques to isolate highly relevant graph entities.
- Familiar with domain-specific data and knowledge related to cybersecurity tradecraft and knowledge resources (enterprise data sources, data extraction tools, data analysis/interpretation techniques, data policy and compliance, and data curation considerations).
- Self-sufficient, self-starter comfortable with working on a collaborative team of highly skilled data scientists and system engineers.
- Able to collaborate with technical mission stakeholders and colleagues for strategic and technical planning.
- Established technical experience and expertise with:
- Python for Data Science (PySpark, Pandas, etc.) and Machine Learning (spaCy, PyTorch, etc.).
- Natural Language Processing (NLP) for text splitting, segmentation, classifiers, labeling, tokenization, and semantic ontology.
- Graph tools such as Neo4j, RedisGraph, or GraphFrames.
- ELK Stack (Elastic Stack): Elasticsearch, Logstash, Kibana.
- ETL to PostgreSQL, MongoDB, Neo4j, Redis.
- Kubernetes, Docker, Kafka.
- Hugging Face.
- AWS, Azure.
- VM (Linux, Ubuntu) configuration for individual and team profiles.
- DevX/Coder.
Position requires active Security Clearance with appropriate PolygraphPay Range: 212,000-267,000
The RealmOne pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Our approach to crafting offers considers various factors to establish an equitable and competitive compensation package. These considerations include, but are not limited to, the extent and intricacy of the role's responsibilities, the candidate's educational background, their work experience, and the specific competencies crucial for success in the role.
RealmOne Benefits:- Healthcare Coverage + Insurance: Medical: Three (3) rich healthcare options through CareFirst with 100% or majority company-paid premiums. Tax-advantaged health savings account available with generous employer contribution. Dental + Vision: 100% employer-paid for employees and family with buy-up option available.
- Retirement + Savings: 401K - 10% TOTAL CONTRIBUTION - 5% safe harbor - 5% annual profit share. Immediate vested, no match required!
- Paid Time Off + More: 4 weeks starting PTO - 11 federal holidays + 2 floating holidays - Paid hours for company-required training.
- Career Growth + Development: Access to FREE 24/7 learning via Udemy - Opportunities to participate in tech councils, industry initiatives, etc. - $7,500 annual Educational & Professional Development Assistance.
- MORE BENEFITS...FOR EVERY LIFESTYLE! - Paid parental leave - Adoption assistance - Annual swag drops - Flexible work schedules - -Generous referral bonus program - Employee appreciation + family-friendly corporate events ...and much more.
