Job Title: Sr. Data Scientist

Location: Arlington, VA – Hybrid Remote (Occasional travel to SCIF Locations in Arlington, Falls Church, Alexandria, or Pentagon)

Eligibility: Candidate must possess an active TS/SCI Clearance

Job Description:

Major Duties/Tasks:

1. Designs, configures, develops, tests, and supports informatics and data science solutions for a wide array of technical use cases.
2. Collaborate with cross-functional teams, including data scientists and software engineers to integrate AI solutions developed by other elements of the DoD community into Search Portfolio products when appropriate.
3. Optimize AI models for performance, scalability, and efficiency, leveraging cloud-based resources and distributed computing frameworks, specifically Apache Spark/Databricks.
4. Ability to adapt code base to also run using GPU enabled Kubernetes clusters.
5. Stay updated on and contribute to the latest advancements in AI research, applying new findings to improve Search Portfolio products.
6. Manage the lifecycle of AI/ML components used in Search Portfolio products from research and development to deployment and optimization.
7. Applies analytical methodologies to diagnose data-related challenges, implement solutions, and evaluate performance.
8. Documents and presents requirements, design alternatives, and findings to team members and clients.
9. Ability to develop strategic, baselined, data modeling processes; ability to accurately determine cause-and-effect relationships.
10. Experience with integrated development environments, data integration, data visualization, data mining, and analysis tools.
11. Maintains and guides the development of common libraries and tools used by multiple teams.
12. Aids in formulating a strategy on how to achieve rapid prototyping.

Required Education:

- Bachelor’s degree plus 7-10 years’ experience or a master’s degree plus 5 years of experience.

Clearance:

- Possess a minimum of an active Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI) eligibility.

Required Skills/Experience:

1. Experience with Machine Learning - ML (natural language processing, computer vision, statistical learning theory, …).
2. Hands-on experience with Natural Language Processing (NLP), Large Language Models, text embedding, semantic query, use of generative AI for text, and retrieval augmented generation (RAG).
3. Familiarity with data preprocessing, feature engineering, and model evaluation techniques essential for machine learning projects.
4. Strong understanding of various ML algorithms, including supervised and unsupervised learning, reinforcement learning, and neural networks.
5. Experience with version control systems like Git, enabling effective collaboration and code management.
6. Experience in an ML engineer or data scientist role building ML models.
7. Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility.
8. Experience using Apache Spark/Databricks distributed compute environments for AI/ML workloads.
9. Experience handling petabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, and working with GPUs to develop models.
10. Experience with cloud-based data persistence products, especially RDS PostgreSQL and PostgreSQL extensions such as pgvector.
11. Experience persisting vectorized data from text embedding processes using Elastic and/or OpenSearch, in addition to vector enabled RDBMS like pgvector enhanced PostgreSQL.
12. Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.