Data Scientist leveraging machine learning to develop personalized customer experiences at Capital One. Collaborating with cross - functional teams using advanced technologies across billions of customer records.
About the role
- Data Scientist II at LexisNexis applying statistical analysis and building predictive models for fraud and credit risk. Collaborating with teams to enhance existing products and provide actionable insights.
Responsibilities
- Understand and execute analytic plans with the appropriate statistical or modeling technique.
- Conduct analyses supporting existing and new product development or customer sales opportunities.
- Assemble, merge and parse large amounts of data to detect meaningful trends and patterns.
- Explore opportunities to enhance existing products with new features or new data sources.
- Develop machine learning models, create model code, and work with internal or external stakeholders to validate accuracy of production code.
- Interpret, document, and communicate analytic work to non-technical audiences.
- Provide support to other data scientists across the organization.
- Critical reviews of data experiments to ensure accuracy, completeness, and feasibility.
- Other duties as assigned.
Requirements
- Master’s degree in statistics, data science, mathematics or quantitative methods
- Experience with big data technologies and applying large scale machine learning techniques
- Experience with version control through GitHub
- Experience with Unix/Linux system architecture and command line tools
- Experience in credit or fraud risk management industry
- At least one year of experience building predictive models using machine learning and conducting data analysis using Python, R, SQL or similar software packages
- At least one year of experience with mainstream programming languages, such as Python, R, Java, or Scala, in a collaborative environment using software development best practices such as version control and testing
- Superior knowledge of data science frameworks, statistical methods and advanced machine learning techniques
- High degree of creative, analytical and problem-solving skills
- Ability to learn quickly and work effectively both independently and collaboratively
- Ability to communicate complex technical or statistical concepts to a non-technical audience
- Ability to apply modern data exploration and visualization techniques to deliver actionable insights.
Benefits
- This job is eligible for an annual incentive bonus
- We are delighted to offer country specific benefits.
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