What are the responsibilities and job description for the Senior Data Scientist position at Core4ce Careers?

Core4ce is looking for Senior Data Scientists to join our team supporting the CDAO effort, which is responsible for the acceleration of the DoD's adoption of data, analytics, and AI to generate decision advantage from the boardroom to the battlefield. The CDAO is the lead for all AI work within the DoD.

If you would like to know a bit more about this opportunity, or are considering applying, then please read the following job information.

Responsibilities

Design, configure, develop, test, and support informatics and data science solutions for a wide array of technical use cases.
Collaborate with cross-functional teams, including data scientists and software engineers, to integrate AI solutions developed by other elements of CDAO or the DoD community into Search Portfolio products when appropriate.
Optimize AI models for performance, scalability, and efficiency, leveraging cloud-based resources and distributed computing frameworks, specifically Apache Spark / Databricks. Ability to adapt code base to also run using GPU-enabled Kubernetes clusters.
Stay updated on and contribute to the latest advancements in AI research, applying new findings to improve Search Portfolio products.
Manage the lifecycle of AI / ML components used in Search Portfolio products from research and development to deployment and optimization.
Apply analytical methodologies to diagnose data-related challenges, implement solutions, and evaluate performance.
Document and present requirements, design alternatives, and findings to team members and clients.
Develop strategic, baselined data modeling processes; accurately determine cause-and-effect relationships.
Maintain and guide the development of common libraries and tools used by multiple teams.
Aid in formulating a strategy on how to achieve rapid prototyping.

Requirements

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

Experience with ML fields, e.g., natural language processing, computer vision, statistical learning theory.

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).

Familiarity with data preprocessing, feature engineering, and model evaluation techniques essential for machine learning projects.

Strong understanding of various machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and neural networks.

Experience with version control systems like Git, enabling effective collaboration and code management.

Experience in an ML engineer or data scientist role building ML models.

Experience writing code in Python, R, Scala, Java, C with documentation for reproducibility.

Experience using Apache Spark / Databricks distributed compute environments for AI / ML workloads.

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.

Experience with cloud-based data persistence products, especially RDS PostgreSQL and PostgreSQL extensions such as pgvector.

Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.

Active TS (SCI Eligibility) Required

All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, age, marital status, pregnancy, genetic information, or other legally protected status.

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