This a Full Remote job, the offer is available from: United States, District of Columbia (USA), New Jersey (USA)
Mathematica applies expertise at the intersection of data, methods,
policy, and practice to improve well-being around the world. We collaborate
closely with public- and private-sector partners to translate big questions
into deep insights that improve programs, refine strategies, and enhance
understanding. Our work yields actionable information to guide decisions in
wide-ranging policy areas, from health, education, early childhood, and family
support to nutrition, employment, disability, and international development. Mathematica
offers our employees competitive salaries, and a comprehensive benefits
package, as well as the advantages of being 100 percent employee owned. As an
employee stock owner, you will experience financial benefits of ESOP holdings
that have increased in tandem with the company’s growth and financial strength.
You will also be part of an independent, employee-owned firm that is able to
define and further our mission, enhance our quality and accountability, and
steadily grow our financial strength. Learn more about our benefits here.
At
Mathematica, we take pride in our commitment to diversity. Building an
inclusive culture that draws on the individual strengths of employees from
different ethnic backgrounds, cultures, lifestyles, abilities, and experience
is key to our success.
We are
looking for a Data Scientist who will derive meaning from data through
the creation and deployment of data-driven approaches to solve problems and
answer important policy questions for clients. A Data Scientist owns data
processing and analysis tasks and supports more senior level data science staff
in implementing statistical, machine learning, generative AI, and other data
science methods for use in research reports, internal systems, or client
systems. Data Scientists will work on all aspects of the data science project life
cycle, including understanding client needs, building data pipelines,
monitoring data quality, developing documentation, creating visualizations,
brainstorming modeling approaches, and implementing those models. Our data
scientists underpin our company's core offerings in program improvement, policy
assessment, and data science, which yield crucial evidence and information for
policy and decision makers. This
position will work remotely or flexibly in one of our office locations.
The ideal
candidate for this open Data Science position has a strong interest in applying
their skills to healthcare and a strong statistical background in causal
inference and supporting methodologies such as imputation, matching,
weighting, regression, quasi-experimental methods, and synthetic-comparison
methods, among others. In addition to the required technical skills below, our
healthcare-focused data scientists strongly benefit from additional knowledge
of SQL or Scala, experience with big data analysis platforms such as Databricks
or Snowflake, and familiarity with healthcare datasets such as Medicare or
Medicaid claims and enrollment data and electronic medical records.
Example
projects include:
• Evaluate and monitor the impacts of an alternative payment model for primary care in terms of care quality, cost, and health outcomes for diverse beneficiaries, using claims from thousands of primary care practices across the country. Use the same data to predict future hospital costs and behavior.
• Develop and evaluate a reproducible benchmarking pipeline to compare state healthcare spending against peer markets nationwide, harmonizing multi-source claims and Census data, applying statistical matching to select comparable regions, and normalizing spending through risk-adjusted regression models to support state rate-setting decisions.
• Build
and evaluate interpretable machine learning models to predict clinical care
tiers from health assessment data, supporting state healthcare program's
transition to a new assessment tool. Partner with subject-matter experts to
engineer clinically meaningful features from raw assessment items and apply
stratified sampling and diagnostics to deliver transparent models suited to
high-stakes eligibility and reimbursement decisions
Specifically,
this Data Scientist contributes to team-based projects by:
• Conducting
causal, predictive, and descriptive analyses
• Writing
and maintaining programming systems in languages such as Python and R to build
and evaluate models
• Developing
reliable data pipelines to obtain, combine, and transform datasets on
cloud, internal, and client servers
• Communicating
technical results to diverse stakeholders including clients and cross-functional
teams
• Developing
and maintaining technical and methodological documentation
• Co-developing
analysis plans with a senior data scientist or researcher
• Leading
and managing small teams and tasks with oversight from a more senior staff
member
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