Biostatistics & Data Analytics Specialist

MAXIMUS

Virginia (MN)

On-site

USD 59,000 - 124,000

Full time

14 days+

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Job summary

Maximus is seeking a data analytics professional to develop advanced methods for analyzing operational data and delivering actionable insights for stakeholders and partners. You will serve as a central data/analytical contact across multiple projects, guiding partners on performance and maturity of solutions while building scalable ETL/ELT pipelines using SQL Server and Databricks.

You will craft analysis-ready datasets, create Power BI dashboards, and apply ML techniques to forecast readiness

Qualifications

Bachelor's degree in related field.
5-7 years of relevant professional experience required.
Equivalent combination of education and experience considered in lieu of degree.
Bachelor's degree with one to two (1-2) years of experience in quantitative science, social science, or a related discipline.
Proficiency with Microsoft Office programs, including Word, Excel, and Access.
Working knowledge of SQL Server/SQL/T-SQL, including querying, joins, indexing basics, and relational schemas.
Hands-on experience or strong exposure to Databricks and Apache Spark, preferably PySpark, or comparable scalable data preparation systems.
Foundational programming skills in Python or R for analysis, data manipulation, and machine learning workflows.
Understanding of data engineering concepts, including ETL/ELT, data modeling basics, data quality checks, reproducible pipelines, and version control.
Experience building visual analytics with Power BI, including reports, datasets/semantic models, and DAX fundamentals.
Familiarity with Power Apps and Power Automate for workflow integration.
Basic familiarity with NLP and Large Language Models, including typical use cases and data requirements.
Ability to communicate clearly with stakeholders and translate mission needs into data requirements and analytical outputs.

Responsibilities

Develop and deploy advanced methods to analyze operational data and derive meaningful, actionable insights for stakeholders and business development partners.
Function as point of contact for data and analytical usage across multiple projects, and guide operational partners on product performance and solution improvement/maturity options.
Analyze extracted data, identify trends and provide insights and analyses around operations and project data.
Develop and implement new metrics, functions, and scripts as KPIs as needed.
Code to defined requirements to segment populations from large enterprise datasets, verify data accuracy, and output files per specifications.
Create and maintain all documentation including obtaining and collecting artifacts as needed.
Ad hoc tool development to support operational and under served analytical areas.
Learning emerging technologies and systems of need for company initiatives.
Activities to support team communication and strategy implementation (meetings, etc.).
Project management activities.
Acquire, integrate, and prepare data from multiple sources to enable operational reporting, readiness analytics, and decision support.
Design and implement ETL/ELT pipelines using SQL Server and Databricks leveraging Apache Spark/PySpark for scalable batch processing and data transformation.
Develop and maintain curated, analysis-ready datasets with attention to data quality, lineage, and repeatability.
Optimize data processing performance and contribute to reliable scheduling, orchestration, and monitoring of recurring workloads.
Apply statistical methods, data mining, and machine learning to generate actionable insights, forecasts, and predictive analytics relevant to military missions and readiness.
Create dashboards and analytical products using Power BI, including semantic modeling and measures to support consistent metrics and reporting.
Support low-code solutions by integrating data products into Power Apps and automations using Power Automate.
Contribute to text and language-focused use cases by preparing and analyzing unstructured data.
Demonstrate familiarity with LLMs and agent concepts and assist senior team members in implementing these capabilities where appropriate.
Document data sources, transformations, assumptions, and analytical methodologies to support transparency and operational continuity.