Data Science Manager

Allegheny County Department of Human Services•Pittsburgh, PA

23h

About The Position

At Allegheny County Department of Human Services (DHS), the mission is to improve the welfare of the County’s most vulnerable residents. DHS operates, influences, and funds essential services worth over $1 billion that more than 200,000 residents depend on each year. DHS has a national reputation for using analytics and technology to deliver more effective and efficient public services. 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 vulnerable residents. The data science team owns DHS’s measurement problems and predictive models, with a team charter focused on creating feedback loops on program efficacy, augmenting human judgment to improve operations, and developing reusable software for inference at scale. The Data Science Manager will collaborate with the Analytics team, Technology team, program managers, and senior leadership to identify what works, iterate on service delivery approaches, improve decision-making, build software, and convert analytics into automated products.

Requirements

Core competency in Python.
Core competency in abstract, hierarchical design.
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.
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).
Clear, organized thinkers about complicated empirical questions.
Bias toward simplicity over methodological complexity.
Sound grasp of the fundamentals in their field.
Intellectually curious and fearless about tackling difficult, unsolved problems.
Balances speed of delivery with upholding high standards on quality.
Maintains a flexible approach to problem solving, prioritizing impact over technical complexity.

Responsibilities

Lead and support a small team of data scientists.
Construct software for leveraging integrated human services data.
Partner with academics to drive research that improves outcomes.
Create feedback loops on performance by learning about program efficacy and informing funding commitments.
Augment human judgment to improve operations and optimize resources.
Develop high-quality reusable software for delivering inference at scale.
Collaborate with analytics, technology, program managers, and senior leadership.
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.