Okay, I've searched for Director-level Data Analytics roles in Manhattan, NY, requiring a Master's degree, full-time schedule, and 5+ years of experience in data management and analytics. I have found 42 positions for you that match these criteria.

Sure. Here's the analysis:

Job Analysis:

The EPMO Data Analytics Director role is fundamentally about leading data-driven strategies to enhance operational efficiency and program effectiveness within New York City's Human Resources Administration (HRA) and Department of Homeless Services (DHS). This position is tasked with harnessing complex data sets, driving analytical innovation, and managing cross-agency collaborations to support critical social service programs tackling poverty and homelessness. Beyond technical proficiency in data mining, predictive analytics, and database management, the role demands strategic oversight of multiple projects with high analytical complexity. The candidate must navigate both internal dynamics — coordinating with ITS, OLA, and other city agencies — and external partnerships through MOUs focused on data sharing and integration. Success in this role involves improving data accuracy and operational outcomes, reducing manual processes, and enabling timely, data-supported decision-making for large-scale public programs. Leadership skills are vital, as the Director manages an analytics team and drives change management efforts across the organization. A master's degree or equivalent experience combined with executive-level supervisory experience is required to ensure the candidate can lead sophisticated analytical initiatives and influence agency leadership effectively. The role demands comfort with ambiguity, balancing innovation with practical deliverables, while aligning technological advancement with public service goals.

Company Analysis:

The Department of Social Services (DSS) in NYC, encompassing HRA and DHS, operates as a critical governmental entity charged with addressing poverty, income inequality, and homelessness for millions of New Yorkers. The agency represents a large-scale, mission-driven organization deeply embedded in public welfare, which inherently requires coordination across multiple government layers and community partners. Its market position is that of a stable, essential public service provider utilizing data and technology to modernize traditional social services. The culture, inferred from its operational mandate, likely values collaboration, inclusivity, and a high degree of accountability coupled with a public service ethos. Given the agency’s scale and complexity, a candidate in this role should expect a fast-paced environment that demands flexibility, innovation, and sensitivity to the social impact of their work. The Data Analytics Director sits at a strategic intersection within the EPMO, which directly supports the agency leadership’s priorities by translating data insights into actionable program improvements and IT initiatives. This role has significant visibility, requiring cross-agency negotiation and representation at high levels, reflecting the importance of diplomacy and strategic communication. Ultimately, the position is crucial for advancing the agency’s adoption of evidence-based approaches and technological modernization to improve service delivery and outcomes for vulnerable populations.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you led a team to implement a complex data analytics project that involved multiple stakeholders with competing priorities. How did you manage the collaboration and ensure successful delivery?
• Behavioral: Describe a situation where you had to negotiate a data sharing agreement with an external government agency or partner. What challenges did you face and how did you resolve them?
• Behavioral: Can you provide an example of when you identified a process inefficiency through data analysis and how you drove change to address it?
• Behavioral: Share an experience where you had to present technical findings to non-technical leadership. How did you tailor your communication to ensure understanding and buy-in?
• Technical: How would you approach designing a predictive analytics model to improve timely and accurate payments for social service programs? What data sources and methodologies would you consider?
• Technical: Explain your experience with managing large-scale databases and performing data matching or data quality initiatives. What tools and techniques have proven most effective?
• Technical: What best practices do you follow to ensure data integrity and confidentiality when working with sensitive client data across multiple agencies?
• Technical: How have you applied geospatial analytics in a social services or public sector context? What insights were gained and how did they impact decision-making?
• Situational: Imagine you discover a critical data discrepancy between two partner agencies that could delay housing assistance payments. How would you address this issue and coordinate a resolution?
• Situational: You are overseeing multiple projects with limited resources and tight deadlines. How do you prioritize and allocate your team’s workload without compromising quality?
• Situational: Suppose a newly implemented technology solution is not meeting the expected performance metrics. How would you investigate and drive corrective actions?
• Company Fit/Motivation: What motivates you to work within a large public social service agency like the NYC Department of Social Services?
• Company Fit/Motivation: How do you see your leadership style aligning with the mission-driven and collaborative culture at DSS?
• Company Fit/Motivation: Considering the scale and complexity of DSS programs, what excites you about leading data analytics initiatives that impact millions of residents?
• Questions for the Candidate to Ask the Interviewer: How does the EPMO measure the success of data analytics projects in driving program improvements?
• Questions for the Candidate to Ask the Interviewer: What are the key challenges the Data Analytics team currently faces when coordinating data exchange agreements with external agencies?
• Questions for the Candidate to Ask the Interviewer: How does DSS support ongoing professional development and innovation within its analytics and IT teams?