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Lead Data Scientist (Causal Inference)

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POST DATE 8/9/2016
END DATE 10/9/2016

Stanford University Stanford, CA

Stanford, CA
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Stanford University

Lead Data Scientist (Causal Inference)

Job Number: 72054

Lead Data Scientist

The Stanford Immigration Policy Lab (IPL) seeks to address the inequalities faced by immigrants in order to improve their lives and our communities. We use a set of advanced analytical tools and rigorous data-driven methods to systematically understand the causal impacts of the diverse policies and programs that affect immigrants throughout the world. We evaluate policies and programs to inform the policy-making community. Our faculty and team of researchers work in a highly collaborative environment. We directly engage community-based organizations and local, state and federal governments to test the effectiveness of policies that ultimately impact millions of immigrants and the economic and social prosperity of the countries where they live. We provide reliable knowledge about whether programs work, fail, or backfire, and for whom and why. This knowledge helps to inform ongoing policy debates and to design more effective immigration policies for the future. We are growing rapidly and are looking for energetic and highly motivated individuals to join our team.

Collecting, analyzing, and visualizing data is essential to the mission of the IPL. We are looking for a full-time Lead Data Scientist to provide analytical expertise across our research programs. Reporting to the Executive Director and working closely with the Faculty Co-Directors, the Lead Data Scientist will be engaged in all aspects of the research process from research design and data collection to producing publishable quality data visualizations. The Lead Data Scientist will be responsible for creating, managing, and updating datasets, assuring data and analysis meet rigorous replication standards, and exploring new and creative data sources and collection methods. The Lead Data Scientist will work closely with faculty and staff to develop research designs, specify models, and conduct/interpret analyses. We expect that the Lead Data Scientist will receive co-authorship on these papers. We are looking for candidates who have the ability, experience and energy to be the data and statistical lead for a diverse research program focused on experimental and quasi-experimental methods.

Experience working in a social science research setting and extensive training in statistics and data science, specifically causal inference is highly preferred. Demonstrated experience designing and implementing experimental and quasi-experimental research designs is essential. A PhD in a relevant area (e.g., statistics, economics, political science) is highly desired.

Candidates selected for in-person interviews will be asked to complete a research design and data science task as part of the interview process.

This is a 100% FTE, one-year, fixed-term position with the possibility of renewal.

Core Duties:

Lead organization-wide data initiatives.
Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
Serve as a resource for non-routine inquiries such as requests for raw data, batch files, or pre-analysis plans.
Communicate with government officials, grant agencies and industry representatives.
Co-author academic articles and policy-briefs.

Education & Experience:
Bachelor's degree and three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

Minimum Qualifications:

Excellent writing and analytical skills.
Ability to prioritize workload.
Substantial experience with analytical programs.

Desired Qualifications:

Relevant social science research knowledge.
Mastery of statistical programs R and Stata.
Mastery of methods of causal inference.
Extensive experience with text analysis, machine learning, and databases (e.g., SQL).
Experience with a general programming language (e.g., Python, Ruby)
Experience creating data visualizations for academic publications as well as broad public audiences.
Demonstrated experience managing a wide range of projects and collaborating across various groups and people.

Final offers of employment are contingent upon successful completion of national criminal background check, national sex offender registry search and, where applicable, driving record.

Stanford 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.

Job: Research

Job Series: Research Data Analyst 2

Location: School of Humanities and Sciences

Schedule: Full-time, 1-Year, Fixed Term position, with the possibility of renewal.

Classification: I

To be considered for this position please visit our web site and apply on line at the following link:

Stanford 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.