Senior Data Analyst

4 weeks ago


Lenexa, Kansas, United States CommunityAmerica Credit Union Full time
Job Summary

The Senior Data Scientist will play a key role in shaping the data strategy and driving data-driven decision-making processes within the organization. This position requires a visionary data scientist who collaborates with cross-functional teams, leverages advanced analytical techniques to solve complex business problems, and helps to mentor junior members of the analytics team.

Key Responsibilities
  • Collaborate with stakeholders to identify business challenges and opportunities that can be addressed through data science to improve key business outcomes.
  • Design, develop, and implement advanced statistical models and machine learning algorithms to extract insights from large datasets.
  • Oversee the end-to-end data science project lifecycle, from data collection and preprocessing to model deployment and monitoring.
  • Communicate complex analytical concepts and results to non-technical stakeholders in a clear and concise manner.
  • Mentor a more junior analysts and data scientists, providing guidance and support in developing analytical models and solutions.
  • Stay abreast of the latest industry trends and advancements in data science and incorporate them into the team's work.
  • Collaborate with IT and data engineering teams to integrate data science solutions into existing systems and workflows.
  • Partner with Innovation and Digital transformation teams to architect and build analytics engines capable of driving real-time personalized insights using analytic models.
  • Apply machine learning models and AI to help mitigate fraud at the credit union.
  • Leverage generative AI capabilities and apply solutions to address complex business problems.
Requirements
  • Undergraduate or advanced degree in Mathematics, Statistics, Computer Science, or a related field.
  • Knowledge and experience in applying statistical and machine learning methods including regression, classification, clustering, decision trees, and neural networks.
  • 6-10 years' experience in developing, deploying, and managing analytical and machine learning models in a production environment.
  • Proven track record of successfully leading data science projects from conception to completion.


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