高级数据科学家
Sr. Data Scientist
高级数据科学家,远程办公
禁止第三方猎头!!!!
- 合同制;可能转为正式雇佣
- 100% 远程办公
- 由于我们的政府客户要求,我们只能考虑美国公民或拥有绿卡且在过去5年中有3年居住在美国的候选人。必须能够获得美国联邦政府客户的徽章并通过政府背景调查。
- 禁止第三方猎头!候选人必须自行申请。
职位描述
我们正在寻找一位高级数据科学家来支持我们的政府客户。将通过应用领域知识、统计分析和先进的机器学习技术,从结构化和非结构化数据中创造价值,以解决复杂的医疗保健挑战。
该职位强调机器学习和 AI 系统的端到端开发,包括传统机器学习、深度学习、自然语言处理(NLP)以及现代基于大语言模型(LLM)的架构,如检索增强生成(RAG)和代理 AI 系统。
职责
- 使用结构化和非结构化数据设计、开发和维护机器学习、深度学习和生成式 AI 解决方案,以解决复杂的医疗保健和商业挑战,包括预测分析、自然语言处理(NLP)、检索增强生成(RAG)、代理 AI 系统和企业级 AI 应用。
- 在 AWS(例如 SageMaker、S3、Glue、Bedrock)上构建和部署端到端的 ML 和 AI 流水线,用于可扩展的训练、评估、推理和生产运营。
- 开发和实现高级自然语言处理(NLP)解决方案,包括文本分类、实体识别、主题建模和语义搜索,使用 Bert 和基于 Transformer 的架构等模型。
- 设计、构建和优化企业级检索增强生成(RAG)系统,包括文档摄入、分块策略、元数据增强、嵌入、向量搜索、检索优化和大语言模型(LLM)编排。
- 开发基于大语言模型(LLM)的应用程序,包括提示工程、评估框架和优化技术,以提高准确性、一致性和成本效率。
- 设计和实现基于代理的 AI 系统,利用推理、规划、记忆、工具编排和多步骤工作流来自动化复杂的业务流程。
- 开发 AI 系统与企业平台(如 ServiceNow、Snowflake、Databricks、API、工作流平台和运营系统)之间的集成。
- 为企业级 AI 平台功能做出贡献,包括代理编排、工具执行框架和知识库管理。
查看英文原文
Sr. Data Scientist, Remote
NO THIRD PARTY RECRUITERS!!!!!
- Contract; Potential Contract to Hire
- 100% Remote
- Due to our government client requirements, we can only consider US Citizen or a Green Card holders who have lived in the US for 3 of the last 5 years. Must be able to obtain a US Federal government client badge and pass a government background investigation.
- NO THIRD PARTY RECRUITERS PLEASE! CANDIDATES MUST BE SELF-REPRESENTED.
Description
We are seeking a Sr. Data Scientist to support our Government client. Will create value from structured and unstructured data by applying domain knowledge, statistical analysis, and advanced machine learning techniques to solve complex healthcare challenges.
This role emphasizes end-to-end development of machine learning and AI systems, including traditional ML, deep learning, NLP, and modern LLM-based architectures such as Retrieval-Augmented Generation (RAG) and agentic AI systems.
Responsibilities
- Design, develop, and maintain machine learning, deep learning, and Generative AI solutions using structured and unstructured data to solve complex healthcare and business challenges, including predictive analytics, NLP, Retrieval-Augmented Generation (RAG), agentic AI systems, and enterprise AI applications.
- Build and deploy end-to-end ML and AI pipelines on AWS (e.g., SageMaker, S3, Glue, Bedrock) for scalable training, evaluation, inference, and production operations.
- Develop and implement advanced NLP solutions, including text classification, entity recognition, topic modeling, and semantic search using models such as BERT and transformer-based architectures.
- Design, build, and optimize enterprise Retrieval-Augmented Generation (RAG) systems, including document ingestion, chunking strategies, metadata enrichment, embeddings, vector search, retrieval optimization, and LLM orchestration.
- Develop LLM-powered applications, including prompt engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost efficiency.
- Design and implement agent-based AI systems utilizing reasoning, planning, memory, tool orchestration, and multi-step workflows to automate complex business processes.
- Develop integrations between AI systems and enterprise platforms such as ServiceNow, Snowflake, Databricks, APIs, workflow platforms, and operational systems.
- Contribute to enterprise AI platform capabilities including agent orchestration, tool execution frameworks, knowledge retrieval services, AI governance controls, and reusable AI patterns.
- Design and implement AI evaluation frameworks and quality methodologies to measure response quality, groundedness, relevance, hallucination rates, task-completion effectiveness, and business value.
- Create evaluation datasets, automated testing strategies, benchmarks, and validation pipelines to continuously improve AI system quality and reliability.
- Implement AI observability and monitoring capabilities including tracing, telemetry, evaluation logging, prompt tracking, usage analytics, performance monitoring, and cost optimization.
- Develop dashboards, operational insights, and analytical tools to communicate findings and support data-driven decision making for technical and non-technical stakeholders.
- Implement predictive analytics, statistical modeling, and exploratory data analysis to uncover patterns, trends, and opportunities within healthcare and operational data.
- Evaluate model and AI system performance using appropriate statistical, ML, and GenAI metrics and communicate findings in a clear, actionable manner.
- Collaborate in an Agile environment with Product, Architecture, Engineering, UX, QA, DevSecOps, Business SMEs, and stakeholders to deliver production-grade AI solutions.
Qualifications
- Requires a minimum of six (6) years of relevant experience. Bachelor's degree is required. Master's or PhD preferred.
- Experience in machine learning and statistical modeling, including supervised and unsupervised learning techniques, deep learning, and a solid foundation in probability, hypothesis testing, and regression.
- Demonstrated experience delivering, monitoring, troubleshooting, and supporting production AI systems, including Generative AI, Retrieval-Augmented Generation (RAG), LLM-powered applications, semantic retrieval systems, enterprise AI assistants, or agent-based workflows in enterprise environments.
- Hands-on experience designing and implementing RAG architectures, vector databases, embeddings, semantic retrieval, retrieval optimization, or enterprise knowledge engineering solutions.
- Experience evaluating AI system performance, including retrieval quality, groundedness, response relevance, hallucination reduction, and task-completion effectiveness.
- Experience with AI observability, evaluation frameworks, tracing, telemetry, prompt monitoring, or operational analytics is preferred.
- Advanced programming skills in Python, with practical experience using ML and data libraries such as pandas, NumPy, scikit-learn, PyTorch, and TensorFlow is preferred.
- Experience with AWS cloud and MLOps tooling, including SageMaker, S3, Glue, Bedrock, Lambda, API Gateway, Airflow, and data stores such as Postgres RDS, Redshift and DynamoDB, along with version control (GitHub) and CI/CD pipelines (e.g., Jenkins) is a plus.
- Experience with backend systems and data integration, including data modeling and supporting APIs for web-based and production applications is a plus.
- Strong written and verbal communication skills with the ability to explain complex technical concepts to diverse audiences.
- Ability to work collaboratively across Product, Architecture, Engineering, UX, QA, DevSecOps, and business stakeholders.
- Experience supporting CMS or other federal healthcare agencies is a plus
Please Note:
- Only those individuals selected for an interview will be contacted.
- No calls, inquiries, or Third-Party Vendors please.
- We are an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences. (The ACI Group is unable to sponsor H1B Visas).
- $1000 Referral Bonus - www.aci.com.
Since 1988, The ACI Group, a Baltimore-based staffing firm, has been committed to hiring the industry's leading professionals, and presenting exciting career opportunities. We have access to varied types of contract, permanent and contract-to-perm positions and offer a choice of employment options including a full benefits package.
Originally posted on Himalayas