Entry Level Data Science Military Jobs (NOW HIRING)

MidAmerican Energy Company, a Midwest utility, provides regulated electric and natural gas service to more than 1.6 million customers in Illinois, Iowa, Nebraska and South Dakota. The company owns and operates a portfolio of power-generating assets, approximately 61% of which is wind generation.MidAmerican Energy Company is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or religious creed, age, national origin, ancestry, citizenship status (except as required by law), gender (including gender identity and expression), sex (including pregnancy), sexual orientation, genetic information, physical or mental disability, veteran or military status, familial or parental status, marital status or any other category protected by applicable local, state or U.S. federal law. Employees must be able to perform the essential functions of the position, with or without an accommodation.

Master's degree or foreign equivalent in Data Science, Computer Science, Artificial Intelligence, Mathematics or related field.

3 years of experience with the following: 

Data science 

Data Modeling and Machine Learning modeling, or analytics

Azure Machine Learning

Azure Data Factory

Azure Databricks

Azure DevOps

Azure AI Foundry

Power BI

Programming with Python and PySpark

SQL

Working with large-scale datasets time series and Advanced Metering Data

Git

Agile

Working in the gas and/or electric utility industry; operational systems and data domains including AMI/MDM, OMS/SCADA/EMS, asset management, and market operations.

2 years of experience working with Large Language Models to develop Retrieval Augmentation Generation Systems.

Education and Experience Requirements.  Master's degree or foreign equivalent in Data Science, Computer Science, Artificial Intelligence, Mathematics or related field with 3 years of experience as a Data Science - Lead, Data Scientist, or similar duties under a different job title. 

Specific skills or other requirements: Experience to include 3 years with: data science, Data Modeling and Machine Learning modeling, or analytics; Azure Machine Learning; Azure Data Factory; Azure Databricks; Azure DevOps; Azure AI Foundry; Power BI; programming with Python and PySpark; SQL; working with large-scale datasets time series and Advanced Metering Data; Git; Agile; working in the gas and/or electric utility industry; operational systems and data domains including AMI/MDM, OMS/SCADA/EMS, asset management, and market operations. Experience to also include 2 years working with Large Language Models to develop Retrieval Augmentation Generation Systems.

Hours per week/Pay Range: 40 hours per week; Pay range: $121,181 - $146,700/yr

Address of worksite: 1615 Locust Street, Des Moines, Iowa 50309

Apply to: Lori Rinkert, MidAmerican Energy Company, 4299 NW Urbandale Drive, Urbandale, IA 50322 or lori.rinkert@midamerican.com. EOE

This opening is being posted in connection with a future filing of an application for a permanent alien labor certification. Any person may provide documentary evidence bearing on the application to the U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue, NW, Room N-5311, Washington, DC 20210. 

Job Duties: Collaborate with business stakeholders to identify highvalue use cases that improve operational efficiency, customer experience, reliability, safety, and sustainability across electric and gas operations. Translate use cases into technical roadmaps, quantifiable KPIs, and delivery plans. Design, develop, and deploy machine learning models (predictive, optimization, timeseries, NLP). Perform exploratory data analysis, feature engineering, and model validation. Lead AI solution engineering using Azure OpenAI Service (LLMs), retrievalaugmented generation (RAG) with Azure Cognitive Search/Vector stores, prompt design, grounding with authoritative utility data, and guardrail policies. Build productiongrade AI microservices/APIs, orchestration, and monitoring on Azure, including hallucination mitigation, content filtering, and responsible AI checks. Establish endtoend MLOps/LLMOps pipelines, automated testing, blue/green rollouts, drift detection, model performance/SLA dashboards, and rollback procedures. Build and maintain scalable, secure data pipelines to ingest, transform, and curate data from different systems. Partner with data engineers and architects to uphold data quality, lineage, governance (Unity Catalog), and security across the Azure ecosystem. Communicate findings and operational insights via Power BI dashboards and narrative data products, enabling decisionmakers in operations, planning, supply chain, and customer service. Contribute to best practices, reusable accelerators (feature stores, pipeline templates, model cards), code standards, and knowledge sharing within the Data & Analytics community of practice. Mentor and coach data scientists and engineers; conduct design reviews and provide technical oversight for complex initiatives. Ensure solutions align with utility regulatory, cybersecurity, and privacy requirements, and with corporate Responsible AI and model risk management policies. Partner with Security/Legal to complete risk assessments and approvals; incorporate auditability, explainability, and humanintheloop controls.

Collaborate with business stakeholders to identify highvalue use cases that improve operational efficiency, customer experience, reliability, safety, and sustainability across electric and gas operations. Translate use cases into technical roadmaps, quantifiable KPIs, and delivery plans. Design, develop, and deploy machine learning models (predictive, optimization, timeseries, NLP). Perform exploratory data analysis, feature engineering, and model validation. Lead AI solution engineering using Azure OpenAI Service (LLMs), retrievalaugmented generation (RAG) with Azure Cognitive Search/Vector stores, prompt design, grounding with authoritative utility data, and guardrail policies. Build productiongrade AI microservices/APIs, orchestration, and monitoring on Azure, including hallucination mitigation, content filtering, and responsible AI checks. Establish endtoend MLOps/LLMOps pipelines, automated testing, blue/green rollouts, drift detection, model performance/SLA dashboards, and rollback procedures. Build and maintain scalable, secure data pipelines to ingest, transform, and curate data from different systems. Partner with data engineers and architects to uphold data quality, lineage, governance (Unity Catalog), and security across the Azure ecosystem. Communicate findings and operational insights via Power BI dashboards and narrative data products, enabling decisionmakers in operations, planning, supply chain, and customer service. Contribute to best practices, reusable accelerators (feature stores, pipeline templates, model cards), code standards, and knowledge sharing within the Data & Analytics community of practice. Mentor and coach data scientists and engineers; conduct design reviews and provide technical oversight for complex initiatives. Ensure solutions align with utility regulatory, cybersecurity, and privacy requirements, and with corporate Responsible AI and model risk management policies. Partner with Security/Legal to complete risk assessments and approvals; incorporate auditability, explainability, and humanintheloop controls.