Chief of Data Analytics, Methodology, and Integration

Chief of Data Analytics, Methodology, and Integration

The Hoover Institution at Stanford University is seeking qualified candidates for the full-time position of chief of data analytics, methodology, and integration. To ensure your application information is captured in our official files for immediate access to your resume, you must apply to and in the key word search box, indicate Requisition #104561.

A cover letter and resume are required for full consideration.

WORK ARRANGEMENT: Hybrid

About Stanford University’s Hoover Institution: The Hoover Institution on War, Revolution, and Peace is a public policy research center devoted to the advanced study of economics, politics, history, and political economy—both domestic and foreign—as well as international affairs. Founded in 1919 by Herbert Hoover before he became the thirty-first president of the United States, the Institution began as a repository of historical material gathered at the end of World War I. The library and archives have grown to be among the largest private repositories of documents on twentieth-century political and economic history. Over time the Institution expanded its mission from collecting archival material to conducting advanced research on contemporary history and economics and applying this scholarship to current public policy challenges. With its eminent scholars and world-renowned library and archives, the Hoover Institution seeks to improve the human condition by advancing ideas that promote economic opportunity and prosperity while securing and safeguarding peace for America and all humanity under the directorship of former Secretary of State Condoleezza Rice.

The Hoover Institution seeks a chief of data analytics, methodology, and integration for SECURE Analytics, a first-of-its-kind national effort authorized by the CHIPS and Science Act of 2022 and funded by the National Science Foundation to enhance the security and integrity of the U.S. research enterprise.

This is a senior-level role for a versatile individual with proven leadership competence who seeks to apply technical skills to the urgent real-world task of safeguarding the continued vitality of US research and innovation in a more challenging global environment.

This role is the sole data professional on the team and will report to the Stanford PI on the project. They will contribute advanced data architecture, engineering, and science skills to the project and directly manage a small team of full-stack developers who will create sophisticated datasets, software tools, deep learning models, and work products that inform and empower key American stakeholders at the intersection of science, technology, and national security. They will facilitate the implementation of leading-edge methodologies in scientometrics, bibliometrics, patent analysis, and risk science to enable granular understanding of evolving global research security risk. Project management experience and interpersonal skills will be crucial to success.

The chief of data analytics, methodology and integration will be required to: design, develop, optimize, and manage systems for transporting, storing, and analyzing high-volume, high-velocity, and high-variety datasets; integrate these datasets with research and scientific data processing pipelines and data analysis at scale; plan and develop strategies, and set standards for designing, implementing, securing and operating such systems; define how the data will be stored, analyzed, integrated and managed by different data entities and IT systems, as well as any applications storing and analyzing data, and refine system performance and functionality; engineer complex Big Data architecture and analytical solutions; and design and develop applications, test and build automation tools.

CORE DUTIES*:

• Architect and engineer the design, development, implementation and maintenance of complex Big Data systems and data-intensive solutions that are scalable, optimized, and fault-tolerant.
• Define and develop guidelines, standards, and processes to ensure data quality, privacy, security, and integrity.
• Elicit, review, and validate data system requirements, including data integration, meta data, and modeling. Design the data architecture and data integration layers.
• Ensure effective integration and security of applications, data, and components to deliver a high quality system capable of supporting real-time data production and complex, data-intensive scientific user analysis.
• Use software development best practices to develop prototypes, proof of concepts for the selected solutions, evaluation metrics, and ensure effective application and integration.
• Will oversee the work of others and work interactively and laterally with other team contributors.

ADDITIONAL CORE DUTIES:

• Build and maintain an ACID-compliant data lakehouse.
• Supervise the development, validation, deployment, and refinement of secure internal and external client-facing platforms with web-based interfaces for search engines, data analysis and visualization.
• Supervise the development, validation, deployment, and refinement of the codebase for analytical platforms on high performance computing systems, ensuring efficient retrieval, analysis, and visualization of complex, interconnected data while maintaining high performance and relevance.
• Supervise the development, validation, deployment, and refinement of the codebase for a graph database analytical platform.
• Supervise the development, training, validation, deployment, and refinement of risk models and deep learning models.
• Supervise the development, training, validation, deployment, and refinement of RAG-optimized LLM agents.
• Evaluate performance of codebase and models.
• Learn and apply novel methods and technologies to solving research problems.
• Contribute to a working environment that is entrepreneurial and team-driven, with a culture of rigorous experimentation in a supportive environment.

MINIMUM REQUIREMENTS:

Education & Experience:

Bachelor’s degree in scientific or analytic field and eight years of relevant experience or a combination of education and relevant experience.

Knowledge, Skills and Abilities:

• Experience using and designing key data structures, algorithms and techniques pertinent to systems that support high volume, velocity, or variety datasets including (data mining, machine learning, NLP, data retrieval, extract, transform, load (ETL) techniques).
• Advanced level knowledge of relational, NoSQL, and graph database systems, and data modeling, structured and unstructured.
• Advanced level knowledge of parallel and distributed data processing techniques and platforms (MPI, Map/Reduce, Batch) and systems.
• Advanced level knowledge in scripting languages, expertise with high performance/systems languages and techniques.
• Experience in benchmark software development and programmable fields/systems, ability to analyze systems and data pipelines and propose solutions that leverage emerging technologies.
• Expertise architecting and deploying reliable data systems and data quality management systems.
• Ability to use and integrate security controls for web applications, mobile platforms, and backend systems.
• Extensive experience in the evaluation, design, and deployment of new tools, frameworks, and patterns to build scalable Big Data platforms.
• Ability to document use cases, solutions and recommendations.
• Demonstrated excellence in written and verbal communication skills.
• Project management skills and ability to understand and apply systems for storing and analyzing datasets.
• Ability to mentor, motivate, and provide guidance to staff on definitive tasks.

Certifications and Licenses: None

PREFERRED REQUIREMENTS:

Education & Experience:

Advanced degree in scientific or analytic field, with a strong foundation in statistics.

Expertise in architecting and engineering data in the public sector, particularly for a federal government agency.

Do you have, or want to develop, these knowledge, skills and abilities?

• Expertise in (No)SQL, graph and vector databases, solving multidimensional, non-linear data problems, deep learning models, and predictive analytics.
• Expertise in meeting data privacy, compliance, and FAIR (findable, accessible, interoperable, and reusable) standards.
• Expertise in developing and implementing software evaluation metrics.
• Expertise in scientometric, bibliometric, and/or patent research methodologies.
• Demonstrated interest or experience in the intersection of data science and public policy, especially in developing rigorous empirical methods to identify risk in the domains of national and economic security.
• Growth mindset, personal initiative to upskill and develop new competencies in a supportive environment.
• Highly organized with keen attention to details; ability to produce high-quality work on deadlines; strong relationship-building skills; ability to interact comfortably and work effectively with others to set timelines, map milestones, meet deadlines, and manage a team with competing priorities and deadlines.

PHYSICAL REQUIREMENTS*:

• Frequently perform desk based computer tasks, seated work and use light/ fine grasping. Occasionally stand, walk, and write by hand, lift, carry, push pull objects that weigh up to 10 pounds.

WORKING CONDITIONS:

• May be required to work non-standard, extended or weekend hours in support of research work.
• Occasional overnight business travel.

WORK STANDARDS:

• Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
• Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
• Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, .

The expected pay range for this position is $189,000 to $190,000 per annum.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website ( ) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.

Studies have shown that people from certain backgrounds are less likely to apply for jobs unless they believe they can perform every job description task. We are most interested in finding the best candidate for the job, and that candidate may come from a less traditional background. We may consider an equivalent combination of knowledge, skills, education, and experience to meet minimum qualifications. If you are interested in applying, we encourage you to think broadly about your background and skill set for the role.

The Hoover Institution at Stanford University is an equal opportunity employer, and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

Hoover Institution, Stanford, California, United States