Enterprise Reporting and Analytics - Data Scientist

Golden 1 Credit Union•Sacramento, CA

About The Position

Golden 1 Credit Union is seeking a Data Scientist to apply advanced analytics, data science, and quantitative techniques to complex enterprise data. The role partners with business leaders and analytics peers to deliver sophisticated analytical solutions that support strategic initiatives, product decisions, business performance, and data-informed decision-making. It translates complex and disparate data into clear, executive-ready insights using strong technical rigor, sound methodology, and effective communication. The position develops and maintains advanced analytical solutions, applies statistical and AI/machine-learning techniques, and works with data engineering teams on pipelines, model integration, and analytics workflows. It also supports experimentation and minimum viable products, develops dashboards and reports, ensures work complies with applicable policies and controls, and identifies opportunities to improve analytics methods and processes. The Data Scientist collaborates with cross-functional stakeholders, provides informal technical guidance to analysts, and contributes subject matter expertise to the Enterprise Reporting and Analytics team.

Requirements

Bachelor’s degree in Computer Science, Mathematics, Statistics, Business Analytics, Data Science, or a related quantitative discipline, or equivalent relevant experience substituted for the degree.
At least 7 years of progressive experience in analytics, data science, or quantitative analysis.
At least 3 years of experience with SAS, SQL, Python, and/or R for statistical analysis and modeling.
At least 3 years of experience applying machine-learning techniques in professional environments.

Nice To Haves

Master’s degree.
Experience supporting analytics solutions within modern data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
Financial services or other regulated-industry experience.

Responsibilities

Design, develop, and maintain advanced analytical and data science solutions supporting business strategy and operational decisions.
Apply statistical and AI/machine-learning techniques to business problems such as segmentation, targeting, forecasting, and optimization.
Manipulate, model, and analyze large, complex datasets using Python, SQL, and related tools.
Contribute to repeatable, scalable analytics frameworks that enable operationalization of data science models.
Partner with data engineering teams on data pipelines, model integration, and analytics workflows.
Support experimentation, pilots, and minimum viable products aligned with defined business use cases.
Translate complex and disparate data into clear data stories that enable data-informed decision-making.
Develop executive-ready dashboards, visualizations, and analytical summaries, including with Power BI.
Prepare recurring and ad hoc analyses, reports, and presentations for management decisions, committee reviews, and enterprise information requests.
Ensure analytical work products comply with applicable standards, policies, regulations, and internal controls.
Monitor internal and external economic, market, and industry trends that may affect business outcomes.
Identify opportunities to improve analytics methods, tools, processes, efficiency, and impact.
Stay current on analytics, risk modeling, AI, and machine-learning trends and best practices.
Design and evaluate experiments, tests, and proofs of concept for analytical approaches, tools, and technologies.
Identify opportunities to automate, streamline, or enhance analytical and risk processes through improved data and modeling solutions.
Collaborate with product managers, analysts, engineers, and other stakeholders to deliver analytics solutions.
Provide guidance and informal mentorship to analysts on technical problem-solving and analytics best practices.
Contribute as a subject matter resource within the Enterprise Reporting and Analytics team.