Associate Data Scientist

Xcel Energy•Minneapolis, MN

2d•Onsite

About The Position

This new role will be part of the Data Analytics Team in Xcel’s customer program organization, supporting critical work around beneficial electrification, demand response, and energy efficiency. The Associate Data Scientist will focus on interpreting complex data using statistical methods, machine learning algorithms, and data visualization techniques. An Associate Data Scientist will play a crucial role in handling and analyzing large datasets to uncover valuable insights. They utilize statistical methods, machine learning algorithms, and data visualization techniques to interpret complex data. By collaborating with cross-functional teams, they will help translate data findings into actionable business strategies, thereby supporting data-driven decision-making processes. Additionally, they may assist in developing predictive models, automating data collection processes, and ensuring data quality and integrity. This position often serves as a foundational step towards more advanced roles in data science, providing essential skills and experience in the field.

Requirements

Bachelor’s degree in computer science, data science, statistics, math or a related analytical concentration is required.
Other bachelor’s degrees with data science relevant certifications will be considered.

Nice To Haves

Energy or utility background
Familiarity with Databricks or other lakehouse platforms
Experience deploying models using CI/CD
Data science or analytics experience in support of marketing teams

Responsibilities

Familiar in working with the two primary languages - SQL and Python. Both are widely used for data analysis, machine learning, and visualization.
Knowledge of machine learning techniques and algorithms.
Experience with data visualization tools like Posit or Power BI.
Understand key concepts related to managing and analyzing large datasets. This includes using statistical methods and machine learning algorithms to derive actionable insights.
Translate the business goals to technical expertise.
Translate data insights into actionable recommendations for decision-makers.
Collaborate closely with more senior team members and learn from experienced colleagues.
Effectively communicate findings to non-technical stakeholders, collaborate with team members, and present to business users.