Education & Experience:
Bachelor degree in a relevant technical field and four years extensive experience or combination of education and relevant technical field experience solving analytical problems using quantitative approaches.
Preferred education with Master degree and experience in data science, machine learning, statistics, computer science, or other related fields.
Knowledge, Skills and Abilities:
Proficiency in manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
Extensive experience in and strong passion for empirical research and answering hard questions with data.
Interpersonal and communication skills to positively convey findings and influence senior leadership & faculty.
Demonstrated experience querying, processing, analyzing, and reporting on large data sets.
Ability to use data retrieval and manipulation tools such as SQL, Brio Query, Business Objects, etc.in conjunction with visual data tools to present data clearly to non-technical audiences.
Familiarity and experience with intermediate statistical methods; advanced proficiency with statistical tools such as SPSS, SAS, R or similar tools.
Ability to tell stories with data using data visualization software such as Tableau, Excel, SPSS, or similar software in conjunction with strong verbal ability.
Ability to use visual data tools to present data clearly to non-technical audiences.
Flexible analytical approach allowing for results at varying levels of precision.
Familiarity with strategic planning concepts.
Excellent project management skills.
Expertise in developing innovative and scalable advanced analytic techniques, tools, and platform to visualize, monitor, and optimize performance of impactful metrics.
Ability to build and optimize predictive analytic models leveraging data science -- machine learning, data mining, statistical inference, etc.
Experience in leading the research and development of machine learning and predictive models such as classification, multivariate regression, clustering, anomaly detection, support vector machine, and neural network.
Hands-on developing text mining algorithms utilizing NLP, semantic modeling, contextual analysis, etc.
Ability to translate unstructured, complex business problems into abstract analytical and mathematical framework and solutions.
Ability to analyze analytics requirements and recommend solutions, techniques and metrics to minimize false positive.
Experience in various programming languages -- Python, R, Java, or SQL.
Proficiency in statistical analysis tools such as NLP, Text Mining, Matlab, or SAS.
Experience working with large data sets and distributed computing framework -- Hadoop, MapReduce, Spark, Pig, Hive, NoSQL, MongoDB, Data Warehouse.
Expertise in software engineering and data analysis principles and skills working on Windows/ Unix/Linux operating systems, Version Control and Office software.
Ability to understand and apply the software development lifecycle.
Ability to lead, mentor, motivate and supervise technical staff.
Certifications and Licenses:
Constantly perform desk-based computer tasks.
Frequently sit, sort, file paperwork or parts, grasp lightly, and use fine manipulation, lift, carry, push and pull objects that weigh 10 pounds or less.
Occasionally write by hand, twist, bend, stoop and squat.
Rarely stand, walk, reach or work above shoulders and use a telephone.
* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
May work extended hours during peak business cycles.
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 Universitys Administrative Guide, http://adminguide.stanford.edu.