Principal Analytics Engagement Consultant

Public Partnerships | PPL•US NY Remote, NY

6d•$162,500 - $214,000

About The Position

Public Partnerships LLC supports individuals with disabilities or chronic illnesses and aging adults, to remain in their homes and communities and “self” direct their own long-term home care. Our role as the nation’s largest and most experienced Financial Management Service provider is to assist those eligible Medicaid recipients to choose and pay for their own support workers and services within their state-approved personalized budget. We are appointed by states and managed healthcare organizations to better serve more of their residents and members requiring long-term care and ensure the efficient use of taxpayer funded services. Our culture attracts and rewards people who are results-oriented and strive to exceed customer expectations. We desire motivated candidates who are excited to join our fast-paced, entrepreneurial environment, and who want to make a difference in helping transform the lives of the consumers we serve. (learn more at www.pplfirst.com). Job Summary: The thesis of the engagement consultant career track is that you’re not just building an analytics ecosystem, your expertise is also in being a key part of solution ideation and business impact enablement. As the Principal Analytics Engagement Consultant you write and publish PPL’s analytics standards for data modeling, the semantic layer, metric definitions, statistical method, documentation, and reproducibility, and those standards bind every team producing analytics. You co-author the enterprise analytics strategy with the VP of Analytics and hold the technical roadmap for the semantic and governance layer. You also hold the entire team to a high standard of execution on systems level thinking and solutioning. When a deliverable, a figure, or a claim is not supported by the evidence, you can stop it, and you are expected to. You are the deciding technical voice on leveling and hiring for the Analytics Engagement Consultant team. You lead PPL’s most consequential engagements: the ones with cross-functional executive sponsorship, regulatory exposure, or material P&L impact. You choose which of these you take on and you own the outcome. You work with PPL Data Architects to ensure the semantic layer, the canonical data models, and the metric definitions meet the minimum quality and rigor expected of the regulatory environment in which PPL operates. You sit with the executive team as a peer. You shape which questions get asked, you reframe the ones that are wrong, and when the evidence disagrees with the room, you use your influence to help change the decision. You defend methodology under regulatory and audit scrutiny, and over time you make PPL known in the Medicaid market as a partner with deep integrity and analytical rigor. You are the quality gate for every analytics team member below you. You review and approve their work, and you develop promising talent toward Principal-level judgment: which method, how much rigor, when to push back, when to stop. You own the evolution of the function’s methodology, tooling standards, and operating model with the VP. You set the culture of the craft, which at PPL means intellectual honesty, partnership with the business, and the willingness to raise your hand when the data does not support an assertion. You stay in the code. When the hardest model needs building, you build it, and your production dbt, SQL, and Python work is the reference implementation others learn from.

Requirements

12+ years of progressive experience in analytics, data science, analytics engineering, or management consulting, including 5+ years at a Staff, Principal, or equivalent level.
Analytical work that shaped enterprise decisions and stood up to regulatory, audit, or executive scrutiny, with specific examples.
Authority over methodology at an organizational level: defined standards, enforced them across teams not managed, and served as final reviewer on high-stakes analysis.
Hands-on depth in contact-center data (Genesys, Five9, NICE, Amazon Connect, or similar): contact-level data modeling, workforce management, routing and multi-channel structure, Erlang calculations.
Production ownership of dbt projects other teams depend on, at enterprise scale.
Senior-level SQL (Python is nice to have), fluency with Databricks and Azure DevOps or equivalent orchestration and CI/CD using dbt.
A record of changing executive decisions through evidence and narrative, including when it was unwelcome.
A record of developing other analytics professionals through mentorship, code review, and craft leadership.
Delivery of solutions that demonstrate strong system-driven strategic thinking.
Bachelor's degree required.

Nice To Haves

Master's degree preferred in computer science or information technology.
Healthcare, Medicaid, or another regulated industry experience, particularly claims, eligibility, payroll, finance, or program integrity.
Consulting partner-track experience (MBB, Big Four advanced analytics) or principal-level analytics work at a mature technology company.
Experience standing up or substantially evolving a semantic or governance layer at enterprise scale.
Python experience.

Responsibilities

Write and publish PPL’s analytics standards for data modeling, the semantic layer, metric definitions, statistical method, documentation, and reproducibility.
Co-author the enterprise analytics strategy with the VP of Analytics and hold the technical roadmap for the semantic and governance layer.
Lead PPL’s most consequential engagements: the ones with cross-functional executive sponsorship, regulatory exposure, or material P&L impact.
Work with PPL Data Architects to ensure the semantic layer, the canonical data models, and the metric definitions meet the minimum quality and rigor expected of the regulatory environment.
Sit with the executive team as a peer, shaping questions, reframing incorrect ones, and influencing decisions when evidence disagrees with the room.
Defend methodology under regulatory and audit scrutiny.
Review and approve the work of analytics team members below you.
Develop promising talent toward Principal-level judgment.
Own the evolution of the function’s methodology, tooling standards, and operating model with the VP.
Set the culture of the craft, emphasizing intellectual honesty, partnership with the business, and the willingness to raise concerns when data does not support an assertion.
Build the hardest models, with production dbt, SQL, and Python work serving as reference implementations.