About our Team:

Opportunity to join a vibrant, collaborative team as a data scientist conducting statistical analysis and building predictive models for a variety of performance outcomes such as fraud and credit risk for one or more industries including (but not limited to) consumer and small business lending, telecommunication, retail, payments, log-ins, and e-commerce. You would be expected to have a firm understanding of data mining, statistical methods, and multiple modeling techniques. As part of the team you would be tasked with finding innovative ways to produce solutions to serve our customers and to continually expand your expertise.

About the Role:

A Data Scientist II should have a basic understanding of best-practice and can execute the methods for projects with supervision. Individuals in this role will continue to provide support to the Data Scientist team members and also begin to lead some analytic efforts.

 

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.

 

Required Qualifications:

• 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.

U.S. National Base Pay Range: $71,600 - $119,400. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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