Sr Data Scientist

Position Overview

The senior data scientist is a member of the Data and Analytics Information Technology team, playing a critical role in supporting Berkshire Hathaway Energy (BHE) business transformations and asset performance initiatives. The data scientist translates business problems into technical and data requirements, collaborates with cross‑functional teams, and contributes to model development, testing, production support, data validation, and data integrity.

• Extract, transform, validate, and load data into data lake and analytics systems such as Microsoft Azure and Power BI.
• Design, build, and product ionize data science proof‑of‑concepts and machine learning models, moving solutions from development to operational environments.
• Lead end‑to‑end data science initiatives in partnership with Product Owners, covering problem definition, data exploration, model development, validation, and deployment.
• Mentor and support a team of data scientists, providing technical guidance, project planning, and stakeholder engagement.
• Collaborate with stakeholders across performance engineering, asset performance, and transmission & distribution to understand data needs and deliver aligned solutions.
• Apply advanced statistical and machine learning techniques to analyze complex datasets, uncover patterns, and develop predictive and prescriptive models.
• Contribute to the company’s data strategy by identifying opportunities to leverage data science for process improvement, operational optimization, and revenue growth.
• Stay current with advancements in data science, machine learning, and GenAI technologies, evaluating and implementing new tools and frameworks.
• Maintain high‑quality documentation, including narrative wikis and version‑controlled technical documentation.
• Operate within an agile environment that supports iterative development and continuous delivery.

• Bachelor’s degree in computer science, mathematics, software engineering, or a related technical field;
  Master’s in data science or related field preferred.
• Five or more years of experience in data science with a proven track record of delivering successful projects.
• Hands‑on experience designing and building data science proof‑of‑concepts using relational databases, APIs, and modern data platforms (e.g., Delta tables). Proficiency with SQL, PySpark, and Python.
• Advanced proficiency in Python and/or R, using libraries for data wrangling (pandas, tidyverse), modeling (scikit‑learn, caret, tidy models), and visualization (seaborn, ggplot2).
• Expertise in at least one core data science domain such as supervised learning, time‑series analysis, or survival modeling, with application to real‑world business problems.
• Experience product ionizing advanced analytics and machine learning models, managing transitions to operational and production environments.
• Strong foundation in descriptive and inferential statistics, including hypothesis testing, confidence intervals, and correlation analysis.
• Hands‑on experience with enterprise data visualization tools (Power BI preferred) and a cloud‑based data platform (Azure and Databricks preferred).
• Excellent verbal and written communication skills, able to convey technical concepts and analytical results to both technical and non‑technical audiences.
• Strong leadership and interpersonal skills, capable of working independently, collaborating effectively within a team, and influencing outcomes without direct authority.
• Demonstrated initiative and resourcefulness, adept at navigating ambiguity, prioritizing work, and delivering results with limited guidance in a fast‑changing environment.
• Experience working in cross‑functional team environments, partnering with engineering, product, and business stakeholders.
• Preferred experience with Spark, Azure Dev Ops, and MLOps practices.

Mid American 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.