Manager, Healthcare Analytics

Cityblock Health

1d•$110,000 - $145,000

About The Position

The Manager, Healthcare Analytics will design and build analytic solutions that will inform business decisions, drive operations, measure our performance and demonstrate our value as a company. They will partner with our Financial, Clinical, and Operational stakeholders to answer complex business and clinical questions that will empower Cityblock to support our members as effectively and efficiently as possible. Cityblock Health is the first tech-driven provider for communities with complex needs—bringing better care to where it’s needed most, block by block. Founded in 2017 on the premise that “health is local” and based in Brooklyn, we are backed by Alphabet’s Sidewalk Labs along with some of the top healthcare investors in the country. Our mission is to improve the health of underserved communities. Importantly, our solutions are designed specifically for Medicaid and lower-income Medicare beneficiaries, and we meet our members where they are, bringing care into the home and neighborhoods through our community-based care teams and Virtual Care offerings. In close collaboration with community-based organizations, local providers, and leading health plans, we are reorganizing the health system to focus on what matters to our members. Equipped with world-class, custom care delivery technology, we deliver personalized primary care, behavioral health, and social services to deliver a radically better experience of care for every member and community we serve. Over the next year, we’ll grow quickly to bring better care to many more members and their communities. To do this, we need people who, like us, believe that everyone should have good care for what matters to them, in their community. Our work is grounded in a belief in the power of a diverse community. To close gaps in care and advance equity in the communities we serve, we have to start with making our own team diverse and inclusive. Our ways of working are characterized by creativity, collaboration, and mutual learning that comes from bringing together a community from diverse backgrounds and perspectives. We strive to ensure that every person on the Cityblock team, and every Cityblock member, feels supported and included as a part of our community.

Requirements

5 years experience in advanced analytics, delivering actionable insights from data, database and big data analytics environments.
3 years of experience developing statistical and machine learning models to answer complex healthcare problems leveraging a wide range of techniques (generalized linear regression, negative binomial regression, k-means clustering, decision trees, etc.)

Responsibilities

Establish credibility and trusted working partnerships with clinical, operational and research leaders to identify levers for broad system change, pull them, and measure and communicate the results.
Design and execute evaluation and measurement plans that effectively assess the outcomes of Cityblock’s programs and initiatives.
Leverage complex statistical and machine learning approaches to demonstrate clinical and financial outcomes associated with Cityblock projects and programs.
Communicates results effectively through presentations, white papers, and peer reviewed publications.
Implement and configure reporting technologies in the Google tech stack, as well as use DBT and SQL
Perform complex descriptive analyses over production-scale data sets to drive business decisions.
Critically interrogate and interpret data to spot patterns and explain data.
Design reports to steer our value-driven business lines, including the development of traditional and non-traditional success metrics.
Work with our clinical operations team to design and implement robust evaluation frameworks.
Ensure data quality and validation and utilize a range of data cleansing techniques to correct both ad hoc and systemic issues.
Drive automation capabilities into reporting solutions.
Retain our analytics repository and other relevant documentation.
Use AI-assisted workflows to accelerate the development, optimization, and management of dbt models and relevant semantic context, while designing and deploying conversational analytics tools to enable intuitive stakeholder self-service.