Sr Data Scientist

Mid American 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. 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. Mid American Energy Company has an exciting career opportunity available. Take the next step in your career and apply now!

Bachelor's degree in computer science, mathematics, software engineering or a related technical field. Master's in data science or related technical field preferred.

Eight or more years of experience in data science, with a proven track record of leading and delivering successful data science projects

Demonstrated hands‑on experience designing and building data science proof‑of‑concepts and working with data from multiple sources, including relational databases, APIs, and modern data platforms (e.g., Delta tables), using SQL, PySpark, and Python.

Advanced proficiency in Python and/or R, with extensive experience using standard libraries for data wrangling (e.g., pandas, tidyverse), modeling (e.g., scikit‑learn, caret, tidy models), and data visualization (e.g., seaborn, ggplot2).

Established expertise in at least one core data science domain, such as supervised learning, time‑series analysis, or survival modeling, with the ability to apply these techniques to complex, real‑world business problems.

Proven experience product ionizing advanced analytics and machine learning models, including transitioning solutions from development to operational and production environments.

Strong practical foundation in descriptive and inferential statistics, including hypothesis testing, confidence intervals, correlation analysis, and related statistical methods.

Hands‑on experience with enterprise data visualization tools (Power BI preferred) and at least one cloud‑based data platform (Azure and Databricks preferred).

Excellent verbal and written communication skills, with the ability to clearly communicate technical concepts, analytical results, and recommendations to both technical and non‑technical stakeholders across multiple levels of the organization.

Strong leadership and interpersonal skills, with the ability to work independently, collaborate effectively within a team, and influence outcomes without direct authority.

Demonstrated initiative and resourcefulness, with the ability to navigate ambiguity, prioritize work effectively, and deliver results with limited guidance in a fast‑changing environment.

Experience working in cross‑functional team environments, partnering with engineering, product, and business stakeholders to deliver data‑driven solutions.

Preferred experience with Spark, Azure Dev Ops, and MLOps practices.

* Mentor and support a team of data scientists by providing technical guidance and thought leadership to ensure successful project execution, while fostering a collaborative and innovative team environment.

Demonstrated experience in team leadership, project planning and management, and stakeholder engagement.

Partner with Product Owners to lead end‑to‑end data science initiatives, from problem definition and data exploration through model development, validation, and deployment.

Apply advanced statistical and machine learning techniques to analyze complex datasets, uncover meaningful patterns, and develop predictive and prescriptive models.

Contribute to the company's data strategy by identifying…