Predictive Analytics Intern

THE SELECTED CANDIDATE WILL BE OFFERED AN HOURLY RATE OF $26.73.

The Administration for Children’s Services (ACS) protects and promotes the safety and well-being of children and families through child welfare and juvenile justice services and community supports. ACS manages community-based supports and foster care services and provides subsidized childcare vouchers. ACS child protection staff respond to allegations of child maltreatment. In juvenile justice, ACS oversees detention, placement, and programs for youth in the community.

ACS’ Division of Policy, Planning and Measurement (PPM) collaborates with every ACS division to bring knowledge to practice. PPM guides systems analysis and strategic systems improvement; assures quality of practice at ACS and its provider agencies; professionalizes the front-line workforce; brings knowledge into practice; provides research and analytic support; and plans and develops new programs and policies.

Within PPM, the Office of Research and Analytics (ORA) produces data, reports and analysis for the agency, as well as for other agencies, the public, and elected officials. ORA works with the New York Statewide Central Register of Abuse and Maltreatment (SCR), and receives reports of abuse or neglect that serve as the starting point for a child protection response. In efforts to assist ACS Child Protective Specialists manage cases, an investigative consultant team can be requested when there are new and/or existing safety or risk concerns for a child(ren) to provide on-time investigative consultation assistance.

PPM is seeking 3 highly motivated and detail-oriented Predictive Analytics Graduate Interns to join our team.

As a Predictive Analytics Graduate Intern, you will support the Predictive Analytics Team within the Office of Research and Analytics, which is in process of building a risk model that will identify child protection cases most in need of investigative consultation. This internship offers an excellent opportunity to work as a member of a team to partner with Child Protective Specialists to identify high-risk cases during the early stages of the investigation so that the right cases get referred and receive timely attention for the most concerning factors.

Key Responsibilities:

- Extensive feature engineering to identify the right factors with predictive power

- Using various imputation methods to identify and deal with missing or inconsistent data entry information

- Use different model-building methodologies to identify the right model for the problem statement and nature of data

- Perform forecasting and data modeling by using appropriate methodologies, evaluating data patterns, monitoring key performance metrics, and performing root cause analysis

- Analyzing features to evaluate feature importance

- Data visualization using software such as Tableau, R or Python

- Draft literature reviews, including researching best practices about the use of predictive models in child welfare, juvenile justice, and other relevant domains such as other social services and criminal justice

- Use current research on fairness, accountability, and transparency from the machine-learning community (i.e., FATML) to inform model development and implementation

Learning Outcomes:

- Gain hands-on experience building data sets (dashboards and reports) for exploratory analysis, and evaluating and defining performance metrics

- Experience building a Predictive Risk Model (PRM) for prioritizing investigative consultation in a government environment

- Enhance abilities in documenting all analyses and reports pertaining to project accomplishments

To apply for the internship, you must be a graduate student and must be currently enrolled or accepted in a graduate program.

Interested candidates should submit their resume by visiting, https://cityjobs.nyc.gov and search for Job ID#772288.

SUMMER GRADUATE INTERN - 10232