Sr Data Analyst

NWEA® is a division of HMH that supports students and educators through research, assessment solutions, policy and advocacy services, professional learning and school improvement services that fight for equity, drive classroom impact and push for systemic change in our educational communities. For nearly 50 years, NWEA has developed innovative pre-K–12 assessments, including their flagship interim assessment, MAP® Growth™ and their reading fluency and comprehension assessment, MAP® Reading Fluency™. For more information, visit NWEA.org to learn more.

HMH is a learning technology company committed to delivering connected solutions that engage learners, empower educators and improve student outcomes. As a leading provider of K–12 core curriculum, supplemental and intervention solutions, and professional learning services, HMH partners with educators and school districts to uncover solutions that unlock students’ potential and extend teachers’ capabilities. HMH serves more than 50 million students and 4 million educators in 150 countries. For more information, visit www.hmhco.com

 

 

Location: Remote (U.S.)

 

 

What you’ll do: 

 

Working in the NWEA Learning Sciences division, the Sr Data Analyst will support the Research and Policy Partnerships team by making complex assessment and product data accessible, reliable, and usable for research, reporting, and organizational decision-making. This role will work with large-scale education datasets and build efficient, reproducible processes for extracting, transforming, and preparing data for analysis. 

 

The Sr Data Analyst will partner closely with researchers and internal stakeholders to understand data needs and translate them into accurate, efficient data solutions. Responsibilities will include: 

 

• Use SQL, Python, and/or R to extract, clean, transform, link, and prepare large-scale assessment and product datasets for research and analysis.  
• Develop and maintain reproducible data workflows and pipelines that improve the efficiency, consistency, and scalability of recurring data needs.  
• Conduct data pulls and analyses of HMH product usage data to support Product Efficacy and Validation and other internal stakeholders.  
• Partner with researchers to translate research questions and analytic specifications into appropriate datasets and data structures.  
• Design and conduct quality assurance procedures to ensure data accuracy, completeness, and consistency.  
• Document data sources, definitions, code, and processes so that workflows are transparent, reproducible, and maintainable by others.  
• Troubleshoot data issues and investigate unexpected patterns or discrepancies in collaboration with researchers and other data experts.  
• Identify opportunities to automate or streamline recurring data processes and improve how the team accesses and uses data.  
• Communicate clearly with technical and nontechnical colleagues about data availability, limitations, definitions, and appropriate use. 

 

 

What you’ll need: 

 

Required: 

 

• Experience: 2-5 years of relevant experience (or combined experience and coursework). 
• Degree: M.S. in statistics, education, psychology, economics, or a related field. 
• Technical:  
  • Expertise in advanced data manipulations, processing large datasets, and optimization of code. 
  • Proficiency in Python and/or R for data processing, manipulation, automation, and analysis. 
  • Strong SQL skills and demonstrated experience querying and manipulating large, complex datasets. 
  • Strong attention to detail and demonstrated ability to independently troubleshoot complex data problems.  
• Experience in:  
  • Designing and conducting quality assurance procedures to ensure correct data and accurate results. 
  • Understanding analytic or research requirements and translating them into appropriate data specifications and solutions.  
  • Documenting technical processes clearly and collaborating effectively with researchers and other technical and nontechnical colleagues.  

 

Preferred: 

 

• Experience working with Snowflake, Postgres, Amazon Redshift, or other cloud-based data warehouse/database systems. 
• Experience working with large-scale education, assessment, longitudinal, or product usage data. 
• Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.  
• Experi