Senior Data Engineer - Data Analytics (Remote eligible) - Mathematica : Job Details

Pay Competitive

Employment type Full-Time

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 using data science and analytics. Our work yields actionable information to guide decisions in wide-ranging policy areas including education, early childhood, family support, nutrition, and employment. 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 employee stock ownership plan (ESOP) holdings that have increased in tandem with the companys 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.

One of Mathematicas core values is a deep commitment to diversity, equity, and inclusion. Our research is more robust because it is informed by a variety of diverse perspectives, and our mission to improve societal well-being is strengthened by a greater understanding of issues and challenges facing the populations we serve. Mathematicas ongoing commitment to diversity and inclusion is woven into our everyday actions, policies, and practices. We are dedicated to maintaining a work environment in which everyone is treated with respect and dignity.

We are looking for an experienced professional with strong data engineering skills and interest in one or more of the following areas: family support, education, child welfare, nutrition, employment, or criminal justice who can support and help grow our portfolio of data analytics work.

The following projects illustrate some of our recent analytics work:

• For the Office of Population Affairs we are using Amazon Web Services (AWS) native tools to design a data collection and reporting system to ingest patient encounters from Family Planning providers and provide data quality checks, summary statistics, and business intelligence reports.
• For the Office of Planning, Research, and Evaluation we are operating a cloud data warehouse, enabling analytic reporting and predictive modeling that leverages administrative and survey data sources in support of program evaluation and data-driven decision-making.
• For the Employee Benefits Security Administration we are monitoring AWS analytics, automating systems testing, and analyzing structured and unstructured data submitted through web forms and PDFs.
• For the Department of Agriculture we are using simulations to estimate how changes in program policies will impact benefit costs, eligibility, and participation in the Supplemental Nutrition Assistance Program (SNAP).

You will work in a multidisciplinary setting that includes staff with degrees in computer science, data science, statistics, economics, mathematics, business, public policy, and related fields. We take pride in our employees and in their commitment to excellence. We encourage staff to collaborate in developing creative solutions to difficult problems. This collegial spirit has helped us earn our reputation for innovative and high-quality work. As a winner of the Excellence in Diversity Award, we know that building an inclusive culture based on the diverse strengths of employees from different backgrounds is key to our success.

• Provide technical guidance and innovative thought leadership around Mathematicas solutions strategy and approach, including staying up-to-date with available technology and tools that are applicable to Mathematicas offerings.
• Design, implement, and maintain databases and data pipelines that are optimized to meet project requirements.
• Lead data analytics tasks such as development of data warehouses, ETL pipelines, data visualizations, etc.
• Provide quality assurance across data analytics tasks.
• Contribute to proposal efforts that support the growth of data analytics work.

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