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Data Scientist - Stanford, United States - Stanford University
Description
Data Scientist (GeoMatch)School of Humanities and Sciences, Stanford, California, United States
Information Analytics
Post Date Nov 29, 2023
Requisition # 101554
Data Scientist (GeoMatch)
Stanford University is seeking to hire a full-time Data Scientist to join the Immigration Policy Lab (IPL) to work on its GeoMatch research portfolio.
Situated within IPL, the GeoMatch team partners with governments to develop and implement an algorithm-based matching tool to connect asylum seekers, refugees, and immigrants to locations within a host country where they are most likely to thrive.
The tool is currently being piloted by one European resettlement agency, and additional pilots are scheduled to launch in Europe and the United States in 2024.
This global research initiative combines high-quality academic research with elements of a social impact tech start-up: codebase development, product design, strategic partnerships, and advances in artificial intelligence.
About the lab
The Immigration Policy Lab (IPL) at Stanford University evaluates policies and designs evidence-driven innovations that help improve the lives of refugees, immigrants, and the communities in which they live.
We work closely with community-based organizations and government agencies to design new programs and tools with the potential to affect the lives of millions of migrants.
Our talented team of faculty, staff, postdocs, and graduate and undergraduate students contribute to an innovative research model that combines the rigor of an academic unit with the efficiency and innovation of a civic-tech lab.
Within the lab, GeoMatch functions with the adaptability of a start-up that develops user-focused software products, while maintaining a commitment to generating rigorous evidence of their impact.
To learn more about GeoMatch and IPL, visit ourAbout the position
We are looking for a full-time Data Scientist to provide technical and analytical expertise to the GeoMatch program.
This position will report to the lead Data Scientist of GeoMatch and work closely with the GeoMatch team of staff and faculty.
The Data Scientist will co-develop and implement machine learning models and algorithms used by our partners as part of their resettlement processes.
They will play a key role in adapting the algorithm to new resettlement processes and research projects.The Data Scientist will also be responsible for creating, managing, and updating datasets and codebases assuring that the data quality, processing, and analysis meet rigorous production standards.
In collaboration with other team members, the Data Scientist will contribute to research designs, conduct/interpret analyses, and explore new and creative data collection and analytical methods.
We are looking for candidates who have the ability and experience to meet the technical requirements of the position and who are enthusiastic about using their skills to build and test a tool with real-world impacts.
The Data Scientist will also have the opportunity to co-author papers that report on the results of the implementations of the algorithm-based matching tool, as well as work with an array of affiliated faculty from top institutions.
IPL is a hybrid (on-campus and remote), highly-collaborative team work environment. Candidates who are available to work in-person are highly preferred. Remote worker agreements may be considered for candidates in the U.S. with the appropriate background and experience.This is a 100% FTE, one-year, fixed-term position with the possibility of renewal depending on funding and performance.
If you believe that this opportunity is a match for your knowledge, skills and abilities, we encourage you to apply.
CORE DUTIES*:
Work closely with other GeoMatch team members (Data Scientist, Software Engineer, and Faculty) to adapt the code used for data processing, machine learning, and optimization to specific contexts based on the needs of external partners
Maintain and optimize machine learning models and algorithms, while exploring and evaluating the performance of alternative ML methods and models as needed
Lead code organization, harmonization, and centralization efforts to ensure the algorithmic matching tool can be used efficiently across multiple contexts and projects
Conduct statistical analyses to measure the projected or actual performance of the algorithmic matching tool in various country contexts
Write and maintain codebooks for country-specific datasets and contexts
Clean, merge, and process raw data from government and non-profit partners
Respond to descriptive and exploratory questions from faculty or partners
Create complex tables and figures for internal analyses and external presentations
Other duties may also be assigned.
EDUCATION AND 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. An advanced degree (Master's or PhD) is highly desired.
KNOWLEDGE, SKILLS, AND ABILITIES:
Substantial experience with MS Office and analytical programs.
Excellent writing and analytical skills.
Ability to prioritize workload
Additional highly desired knowledge, skills and abilities include:
Experience in a quantitative discipline such as economics, finance, statistics, political science, computer science, operations, or engineering.
Experience working with a large and complex code base.
Mastery of R.
Experience implementing machine learning methods and mathematical optimization.
Commitment to and alignment with GeoMatch research goals and IPL's mission.
Demonstrated ability to manage work across many different projects simultaneously, learn skills quickly and efficiently, work well within collaborative and cross-functional team settings, and be highly accountable to deadlines and partner needs.
Experience using version control tools, such as git/GitHub, to collaborate on projects.
Ability to thrive in a lean, start-up environment: able to manage ambiguity and navigate uncertainty and competing priorities while contributing to a supportive, focused and productive team environment.
Strong verbal and written communication skills with the ability to clearly convey information to both technical and non-technical partner organizations.
Additional preferred qualifications include:
PhD or advanced degree in a relevant area (e.g., statistics, economics, operations research, computer science) or 5+ years of relevant work experience in data analysis, machine learning implementation, and operations research.
Experience creating data visualizations for internal project stakeholders and broad public audiences
Experience developing, maintaining, and testing data architecture and pipelines
Experience working on an end-user production software application
Knowledge of immigration policy and related academic literature
Experience in social science research, causal inference methods, or applying statistical tools to address policy problems
How to Apply
We recognize that the job description may not exactly match your qualifications. If you think you may be a good fit, we encourage you to apply. We invite you to apply for this position by clicking on the "Apply for Job" button. To be considered, please submit a cover letter and resume along with your online application.
Your one-page cover letter should briefly describe your background and interest in IPL and the GeoMatch research program, your experience doing data science work in collaborative environments, and your motivation for joining a team using data science for social impact.
Optional:
We also welcome attachments showcasing work samples and portfolios of past projects.
This remote role is open to candidates anywhere in the United States. Stanford University hasfive Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range for this position is $72,000 to $126,000 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.Why Stanford is for You
Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy.
Our culture and unique perksempower you with:
Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
A caring culture. We provide superb retirement plans, generous time-off, and family care resources
A healthier you. Climb our rock wall, or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
Discovery and fun. Stroll through historic sculptures, trails, and museums.
Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more
The job duties listed are typical examples of work performed by positions in this job classifications 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.Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities.
Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at For all other inquiries, please submit a contact form.
Stanford is an equal employment opportunity and affirmative action employer.All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Additional InformationSchedule:
Full-time
Job Code: 4752
Employee Status:
Fixed-Term
Grade:
I
Requisition ID: 101554
Work Arrangement :
Hybrid Eligible, Remote Eligible