Sr. Data Scientist

2 weeks ago

Lenexa, United States CommunityAmerica Credit Union Full time
Summary

The Senior Data Scientist will play a pivotal role in shaping the data strategy and driving data-driven decision-making processes within the organization. This position requires a visionary data scientist who collaborate with cross-functional teams, leverage advanced analytical techniques to solve complex business problems and help to mentor junior members of the analytics team. The ideal candidate will have a strong background in data science, excellent interpersonal skills and a passion for innovation.

Duties & 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.
  • Perform other duties as assigned.
Requirements

Education and Experience 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.
Required Knowledge, Skills and Abilities:
  • Natural sense of curiosity; being able to self-motivate and proactively find unique or actionable insights and solutions leveraging data.
  • Ability to understand business needs and become a leader in enabling data driven business decisions while also having the ability to work successfully in a team environment.
  • Extensive experience with machine learning frameworks and libraries (e.g., Scikit-learn, XGBoost).
  • Extensive experience in a statistical programming language such as Python or R.
  • Experience with building machine learning and AI models in a cloud environment preferably using Databricks
  • Excellent problem-solving skills and the ability to think critically and strategically.
  • Comfortable working in a dynamic environment with multiple concurrent projects.
  • Ability to visualize in advance rough requirements and process necessary to implement new production data science applications.
  • Empathy and passion for leading junior team members through complex analytical projects.
  • Strong communication skills with ability to present ideas and concepts to diverse audiences.
  • Familiarity and experience working with relational databases and SQL.
Preferred Knowledge, Skills and Abilities:
  • Data science experience in the financial/banking sector.
  • Experience with development tools including Jupyter, PyCharm, VS Code, OpenAI/ChatGPT, Azure DevOps, Jenkins, and Docker.
  • Experience with Microsoft Azure cloud environment leveraging ADLS, SQL Server, Cosmos, Azure OpenAI, Cognitive Search, Databricks, and AKS.
  • Experience with notable packages/technologies including LLaVA, XGBoost, scikit-learn, Pandas, Spark and GraphQL.
  • Familiarity with building data pipelines using unstructured and non-relational data stores.
  • Experience writing SQL and developing REST APIs.

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