Data Scientist at CommunityAmerica Credit Union

Lenexa, Kansas, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Apr, 26

Salary

0.0

Posted On

23 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Statistical Modeling, Python, SQL, Data Analysis, Cloud Computing, Problem Solving, Communication, Collaboration, Innovation, Data Engineering, AI, Fraud Mitigation, Generative AI, Data Visualization

Industry

Banking

Description

Summary The 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. 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. 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. 3-5 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. Experience with building machine learning and AI models in a cloud environment preferably using Databricks and Azure Foundry. 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. 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 Foundry, Copilot, 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.

Responsibilities

The Data Scientist will collaborate with stakeholders to identify business challenges and design advanced statistical models to extract insights from large datasets. They will oversee the entire data science project lifecycle and communicate findings to non-technical stakeholders.