Data Science Manager

Allegheny County Department of Human Services•Pittsburgh, PA

1d•$115,000 - $125,000

About The Position

At Allegheny County Department of Human Services (DHS), our mission is to improve the welfare of the County’s most vulnerable residents. We operate, influence, and fund essential services worth over $1 billion that more than 200,000 residents depend on each year, including treatment for mental health and addiction, homeless housing, and child and older adult protective services. Over the past 20 years, we have built a national reputation for being on the cutting edge of state and local governments using analytics and technology to deliver more effective and efficient public services. While we know much more about the use of analytics and software than when we first started, we still have much to learn. Above all, we are convinced that there remain significant opportunities for data and technology to improve the lives of our clients, and for DHS to extend its leadership role in inspiring governments to make similar investments. We’re looking for a manager with a mix of experience or interest in machine learning (predictive modeling) or economics (applied microeconomics and causal inference) to join our data science team as a Data Science Manager. The Data Science Manager will lead and support a small team of data scientists, work to construct software for leveraging nationally recognized, integrated human services data, and partner with world-class academics to help drive research that improves outcomes for our most vulnerable residents. Our bet is that great talent, even in time-limited commitments, can result in a step function improvement in the quality of work in local government. The data science team owns DHS’s measurement problems and predictive models, with a team charter of: (1) creating feedback loops on our performance by learning about the efficacy of programs and interventions and informing DHS’s funding commitments; (2) augmenting human judgement to improve operations and optimize constrained resources, such as case worker bandwidth; and (3) developing high quality reusable software that allows us to deliver inference at scale. The Data Science Manager will collaborate closely with our 40-person Analytics team, Technology team, program managers, and senior leadership to help identify what works and why, iterate and experiment with new approaches to service delivery, improve human decision making, build better software, and convert analytics into automated, extensible products. Strong candidates for the role will be clear, organized thinkers about complicated empirical questions, have a bias toward simplicity over methodological complexity, and possess a sound grasp of the fundamentals in their field. With our nationally recognized integrated data and talented teammates to support empirical work, ideal candidates will be intellectually curious and fearless about tackling difficult, unsolved problems for the department. Candidates should also have experience mentoring or guiding technical staff, supporting project execution, and contributing to team-level standards and practices.

Requirements

Core competency in python and abstract, hierarchical design.
Some experience with statistical and machine learning modeling.
Graduate degree or significant experience in computer science or related field.
Track record of developing high-quality, well-structured, and maintainable software applications.
Experience with applied research and/or industry experience in building machine learning or causal models to answer real-world problems.
Balances speed of delivery with upholding high standards on quality.
Maintains a flexible approach to problem solving, prioritizing impact over technical complexity.
Knowledge of a statistical programming language such as Python, R, or Stata.
Familiarity with a programming language for querying structured data.
Experience providing technical guidance or mentorship.
Experience managing team workload.
Experience coordinating cross-functional work.

Nice To Haves

Interest in machine learning (predictive modeling) or economics (applied microeconomics and causal inference).

Responsibilities

Lead and support a small team of data scientists.
Construct software for leveraging nationally recognized, integrated human services data.
Partner with world-class academics to help drive research that improves outcomes for our most vulnerable residents.
Create feedback loops on performance by learning about the efficacy of programs and interventions and informing DHS’s funding commitments.
Augment human judgment to improve operations and optimize constrained resources, such as case worker bandwidth.
Develop high-quality reusable software that allows us to deliver inference at scale.
Collaborate closely with our 40-person Analytics team, Technology team, program managers, and senior leadership to help identify what works and why.
Iterate and experiment with new approaches to service delivery.
Improve human decision making.
Build better software.
Convert analytics into automated, extensible products.
Provide technical guidance or mentorship.
Manage team workload.
Coordinate cross-functional work.
Develop, test, and QC software to facilitate end-to-end applied research.