The NYU McSilver Institute for Poverty Policy and Research is committed to creating new knowledge about the root causes of poverty, developing evidence-based interventions to address its consequences, and rapidly translating research findings into action through policy and best practices.
We are seeking to recruit a research data scientist for the Institute and with a special focus on our Artificial Intelligence (AI) Hub. The AI Hub at McSilver has been established to investigate how artificial intelligence-driven systems can be used to equitably address poverty and challenges relating to race and public health, and to provide thought leadership on the implications. The AI Hub at NYU McSilver will address a dearth of information about how AI can impact the lives of people in marginalized communities. Among the hub's initial areas of focus will be building on the institute's work to answer whether AI can be used to better predict suicide rates and behaviors by race, geography, income and other demographic variables, with other innovative public health research and interventions to follow.
Reporting to the Chief AI Officer, and working in collaboration with the Director for Research, the Research Data Scientist will lend their expertise, leadership and strategic planning for the continued growth and expansion of research and evaluation projects to the AI data analytic team, They will work with faculty and students on research projects and will be responsible for the pursuit, development, and expansion of research-oriented activities with strategic partners and funders.
Access, validate and analyze information from multiple data sources by developing, validating, and linking various data sets, including high-risk, health, behavioral, as well as public data sets.
Aggregate and analyze population health data, research data, survey data, and other sources to prepare for AI/ML analysis and algorithmic development.
Develop and create documentation regarding the collection, processing, and governance of data sets.
Oversee the data use agreement compliance process and data governance practices as required by regulatory, privacy, and security policies.
Collaborate with data set sources within NYU, government agencies and other research teams outside of NYU to link program data with other health and personnel data to support AI/ML research.
Perform computational and business analytical studies using rigorous data science techniques to provide insight into areas of trending/improvement for suicide risk by race, ethnicity,and other demographic variables.
Provide a quality control program to ensure a high level of quality of results.
Provide programming and subject matter support for refining the development of new approaches and identifying and validating relevant data sets.
Provide advanced statistical support including recommendations for data and predictive models, validation of existing and proposed models, and development of new data and predictive models.
Develop methodology, process data, perform analysis and provide documents in support of websites including, but not limited to, AI Hub Dashboards.
Conduct research and perform analysis (including development/use of predictive models for improving and evaluating suicide risk.
Coordinate and arrange for program data transfer from DHA, MCSCs, MTFs, and other users of various programs.
Develop documentation regarding the processing, governance and provenance of data sets used in research.
Participate in the development and documentation of methodologies for use in publications of AI Hub research.
Research, identify and apply, when available, standardized benchmarks and thresholds and metrics as appropriate.
Support the AI Hub as the lead information resource in the documentation, planning, design, building, implementation, and maintenance of data management systems (e.g. data lake) for the AI Hub.
Collecting data through means such as analyzing existing data sets, survey results or by setting up and managing new studies
Document the methodology for research studies and publications.
Transfer data into a new format to make it more appropriate for analysis
Create new, experimental frameworks to collect, analyze, and categorize data
Build tools to automate data collection, data ingestion, and data processing for AI/ML studies
Search through large data sets for usable information
Create reports and presentations for researchers, faculty, and other uses
Correlate similar data to find actionable results
Master's Degree in Statistics, Mathematics, Computer Science or related quantitative field of study or equivalent combination of education and experience.
REQUIRED SKILLS AND EXPERIENCE:
Demonstrated ability to develop original research in statistics and data science.
Minimum of 5 years experience developing and implementing advanced statistical or data analytical models.
Demonstrated experience conducting data analysis and research using high-risk or restricted data.
Ability to acquire skills/capabilities necessary to meet growing needs/demands of systems/software/hardware.
Ability to critically examine, evaluate, and problem-solve.
Ability to deliver products on time, on schedule, and within budget.
Flexibility and ability to adapt to the rapidly changing and often time-constrained environments.
Able to communicate effectively in written and verbal form.
Demonstrated ability to communicate analytical discoveries and appropriate recommendations/mitigation strategies effectively and clearly to audiences which have limited technical knowledge.
Demonstrated ability to organize/participate/lead working groups to develop analytic products and byproducts or to develop/understand processes leading to effective optimization of analytic efforts.
Demonstrated ability to provide accurate and timely analytical products containing well-reasoned and cogent discussion points, providing leadership with substantiated options or courses of action.
Demonstrated ability to undertake and complete multiple tasks with multiple deadlines simultaneously.
Proven ability to synthesize disparate data from multiple sources and coalesce into an accurate and useful analytic product, incorporating McSilver Institute and AI Hub strategic goals for use by leadership in developing evidence-based and data-driven policy recommendations.
Hands-on experience using Python, Java or other coding languages to develop secure maintainable code.
Expert knowledge of data tools used for statistical analysis and computing, processing large data sets, data visualization, data wrangling, programming, statistics, and predictive modeling, e.g. GCP or AWS stack.
Strong background in selecting, evaluating, pre-processing, and management of data for predictive analytics, statistical reporting, and AI/ML analysis.
The ability to develop and define appropriate methods for data collection and processing, tuning, and provenance and traceability are a plus.
Research ability demonstrated by a strong publication record of journal and conference publications or submitted/accepted papers in top venues.
Demonstrated experience leading an academic research project in data science, with the ability to work independently as part of an AI/ML engineering team, focused on deliverables, outputs, and impact.
Demonstrated ability to develop original research in statistics and data science.
Background in applied AI, predictive analytics, or statistics in healthcare, mental health, public health, social sciences and social work is a plus
Ability to work collaboratively in a multi-disciplinary team.
Active participation in the scientific community.
Strong communication skills.
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $85,000- $115,000. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.
Please note: this is a grant funded position with the opportunity for ongoing renewal reviewed on an annual basis. This position does not qualify for visa sponsorship.
Currently, NYU McSilver is operating on a hybrid schedule, all staff are expected to be on-site 3 days a week.
Please enclose a CV/Resume and cover letter with your application.
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