高级数据科学家
Senior Data Scientist
职位概述
Prometheus Federal Services (PFS) 是联邦卫生机构的值得信赖的合作伙伴。我们正在寻找一名高级数据科学家，通过高级分析、预测建模、数据科学和人工智能解决方案来支持美国退伍军人事务部（VA）的项目。该职位将专注于将复杂的 VA 数据资产转化为可操作的见解，以支持运营决策、医疗成果、数据现代化计划和企业报告。
高级数据科学家将与业务利益相关者、数据工程师、分析师和项目领导合作，设计、开发并实现先进的分析解决方案。理想的候选人应具备统计分析、机器学习、数据工程概念和医疗保健分析方面的深厚专业知识，并有在复杂联邦数据环境中工作的经验。
合理调整说明
要胜任这份工作，个人必须能够顺利完成所有关键职责。可根据需要对有残疾的合格人员进行合理调整，以帮助其完成关键职能。
关键职责和要求
数据科学、高级分析与人工智能/机器学习
· 开发并实施高级分析模型，以识别大型和复杂数据集中的趋势、模式、风险和机会。
- 设计、构建和部署机器学习模型，以支持预测和处方性决策。
- 应用统计技术与数据科学方法，解决复杂的业务和运营挑战。
- 开发预测、分类、聚类、异常检测和优化模型，以支持项目目标。
- 支持人工智能驱动的分析解决方案，以提升运营洞察力、绩效评估和资源规划。
- 评估新兴的人工智能、机器学习和高级分析技术，以确定其在 VA 环境中的适用性。
- 开发模型监控和评估框架，以确保准确性、稳定性、可解释性和性能。
数据探索、准备与特征工程
· 进行探索性数据分析（EDA），以发现模式、异常和关键业务驱动因素。
- 执行数据概要分析和质量评估，以识别影响分析结果的问题。
- 制定特征工程策略，以提高模型性能和业务相关性。
- 准备和转换结构化和半结构化数据集，以便用于分析。
查看英文原文
Position Summary
Prometheus Federal Services (PFS) is a trusted partner of federal health agencies. We are seeking a Senior Data Scientist to support Department of Veterans Affairs (VA) programs through advanced analytics, predictive modeling, data science, and AI-enabled solutions. This role will focus on transforming complex VA data assets into actionable insights that support operational decision-making, healthcare outcomes, data modernization initiatives, and enterprise reporting.
The Senior Data Scientist will collaborate with business stakeholders, data engineers, analysts, and program leadership to design, develop, and operationalize advanced analytical solutions. The ideal candidate brings deep expertise in statistical analysis, machine learning, data engineering concepts, and healthcare analytics, along with experience working within complex federal data environments.
Reasonable Accommodations Statement
To succeed in this job, an individual must be able to satisfactorily perform each essential duty. Reasonable Accommodations may be made to enable qualified individuals with disabilities to perform essential functions.
Essential Duties and Responsibilities
Data Science, Advanced Analytics & AI/ML
· Develop and implement advanced analytical models to identify trends, patterns, risks, and opportunities within large and complex datasets.
- Design, build, and deploy machine learning models to support predictive and prescriptive decision-making.
- Apply statistical techniques and data science methodologies to solve complex business and operational challenges.
- Develop forecasting, classification, clustering, anomaly detection, and optimization models to support program objectives.
- Support AI-enabled analytical solutions that improve operational insight, performance measurement, and resource planning.
- Evaluate emerging AI, machine learning, and advanced analytics technologies for applicability within VA environments.
- Develop model monitoring and evaluation frameworks to ensure accuracy, stability, explainability, and performance.
Data Exploration, Preparation & Feature Engineering
· Conduct exploratory data analysis (EDA) to uncover patterns, anomalies, and key business drivers.
- Perform data profiling and quality assessments to identify issues impacting analytical outcomes.
- Develop feature engineering strategies to improve model performance and business relevance.
- Prepare and transform structured and semi-structured datasets for advanced analytical applications.
- Collaborate with data engineering teams to establish scalable analytical datasets and model-ready data pipelines.
Data Integration, Engineering & Architecture Collaboration
· Partner with data engineers and architects to integrate data across diverse VA systems, databases, APIs, and enterprise platforms.
- Support the design and optimization of data pipelines and analytical workflows.
- Contribute to data modeling efforts that improve accessibility, scalability, and performance of analytical solutions.
- Assist in developing reusable analytical frameworks and data science assets across programs.
- Ensure analytical solutions align with data governance, security, and compliance requirements.
Business Partnership, Strategy & Communication
· Translate business questions, policy objectives, and operational needs into analytical approaches and measurable outcomes.
- Present analytical findings, model outputs, and recommendations to technical and non-technical stakeholders.
- Develop executive-level briefings, data visualizations, and decision-support materials.
- Partner with program leadership to identify opportunities to transition from descriptive reporting to predictive and prescriptive analytics.
- Communicate model assumptions, limitations, and risks to stakeholders in a clear and understandable manner.
Governance, Documentation & Continuous Improvement
· Develop and maintain documentation for analytical methods, models, data sources, assumptions, and validation procedures.
- Support analytical governance and best practices related to model lifecycle management and reproducibility.
- Participate in peer reviews and quality assurance activities for analytical products.
- Continuously evaluate new methodologies and technologies to improve analytical capabilities and program outcomes.
- Mentor junior data scientists, analysts, and technical team members.
Minimum Qualifications
· Bachelor's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Operations Research, Engineering, Healthcare Informatics, or a related field.
- 8+ years of experience in data science, advanced analytics, machine learning, or related technical roles.
- Strong proficiency in Python for data science and machine learning applications (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch, or similar).
- Advanced knowledge of statistical methods, predictive modeling, and machine learning techniques.
- Strong proficiency in SQL for data extraction, transformation, and analysis.
- Experience developing and validating machine learning models, including classification, regression, clustering, forecasting, and anomaly detection.
- Experience conducting exploratory data analysis and communicating insights to diverse audiences.
- Familiarity with model evaluation techniques, performance metrics, and validation methodologies.
- Experience working with large-scale structured and semi-structured datasets.
- Understanding of data engineering concepts, including ETL/ELT processes, data pipelines, and cloud-based data platforms.
- Strong problem-solving, critical thinking, and analytical skills.
- Excellent written and verbal communication skills.
- Authorized to work in the U.S. indefinitely without sponsorship.
- Ability to obtain a Public Trust clearance.
Preferred Qualification
· Master's degree or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Operations Research, Engineering, Healthcare Informatics, or a related discipline.
- Experience supporting the Department of Veterans Affairs (VA), Veterans Health Administration (VHA), or other federal healthcare agencies.
- Experience working with healthcare, clinical, claims, operational, or population health datasets.
- Experience with cloud-based analytics platforms such as Azure Synapse, Azure Machine Learning, Databricks, AWS, or comparable environments.
- Familiarity with Power BI, Tableau, or other business intelligence and visualization platforms.
- Experience supporting enterprise data modernization, governance, or digital transformation initiatives.
- Experience developing explainable AI (XAI) and responsible AI solutions in regulated environments.
- Experience mentoring and leading technical teams or analytical workstreams.
Compensation & Benefits
PFS offers a benefits package that may include health, dental, and vision coverage; flexible spending accounts; disability and life insurance; a retirement plan; paid time off; and other programs to support employees and their families. Learn more about PFS Benefits.
The posted salary range represents PFS's good-faith estimate for this role. Actual compensation offered will be determined by a combination of factors, including but not limited to: the candidate's education, knowledge, skills, competencies, and experience;internal equity; geographic location; and contract and organizational requirements. PFS is committed to fair, consistent, and equitable compensation practices across the organization, and offers are calibrated to maintain internal pay equity while remaining competitive in the external market.
Salary Range: $100,000 - $140,000Equal Employment Opportunity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, parental status, national origin, age, disability, genetic information, political affiliation, military service, or other status protected by law.
Accommodations
PFS is committed to providing equal employment opportunities to all applicants. If you require a reasonable accommodation during the application or interview process, please contact us at . Reasonable accommodations are available to ensure applicants with disabilities have equal access to the hiring process, in accordance with the Americans with Disabilities Act (ADA) and applicable laws.
Workplace Health, Safety, and Compliance
This position may be subject to client‑specific or government‑mandated vaccination, health, or safety requirements, which may change over time.
Texting Privacy Policy and Information:
- Message type: Informational; you will receive text messages regarding your application and potentially regarding interview scheduling.
- No mobile information will be shared with third parties/affiliates for marketing/promotional purposes.
- Message frequency will vary depending on the application process.
- Msg & data rates may apply.
- Opt out at any time by texting "stop".
Originally posted on Himalayas