Fraud Data Scientist
Location - Remote - London
RSA oﬀers mission-driven security solutions that provide organizations with a uniﬁed approach to managing digital risk that hinges on integrated visibility, automated insights and coordinated actions. RSA solutions are designed to eﬀectively detect and respond to advanced attacks; manage user access control; and reduce business risk, fraud and cybercrime. RSA protects millions of users around the world and helps more than 90 percent of the Fortune 500 companies, and every branch of the U.S. federal government, thrive and continuously adapt to transformational change. For more information, go to rsa.com.
Opportunity to join a vibrant, collaborative team as a fraud 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) Banking, retail, 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. You will directly support some of the largest banks in the world.
Assemble, merge and parse large amounts of data to detect meaningful trends and patterns
Explore opportunities to enhance existing data with new features or evaluate new data sources to improve analysis outcomes
Consult with internal and external clients regarding analytic solution implementation, score calculations, analytic output, and statistical techniques
Interpret, document and successfully communicate analytic work and/or results to stakeholders, including those in non-analytic roles
Conduct analysis and produce reports in support of existing and new product development and/or customer sales
Understand and execute analytic plans with the appropriate statistical or modeling technique
Proactively identify and communicate data quality issues and successfully work with other teams to implement solutions
Provide support to other senior data scientists across the organization
Critical reviews of data experiments to ensure accuracy, completeness, and feasibility
Identifying and deploying new algorithms or combinations of algorithms in creative ways to achieve performance improvement
Devising new approaches to solve difficult statistical modeling problems. This includes new model concepts and designs, such as different targets and objective functions, and new or different uses of data sources.
Other duties as assigned
Bachelor’s degree in statistics, data science, mathematics or quantitative methods and at least 4 years of relevant work experience
At least two years of experience conducting data analysis using R, Python or similar packages
Knowledge of how machine learning is used to build predictive models
Strong mathematical and statistics skills
Demonstrate competencies in relevant Data Science frameworks.
At least two years of experience with mainstream programming languages, such as Java, Python, and/or Scala.
Experience with data manipulation techniques
High degree of creative, analytical and problem-solving skills
Ability to learn quickly and communicate effectively
Ability to work effectively both independently and collaboratively
Willingness to adapt to new techniques and an innovative attitude towards finding solutions
Fluency with presentation and document programs such as PowerPoint, Word, Excel
Strong interpersonal and communication skills (both written and oral):
Ability to communicate complex technical or statistical concepts to a non-technical audience.
Work as part of a team and collaborate with colleagues while maintaining highest levels of respect and positive team spirit.
Expert in SQL
Master’s degree in statistics, data science, mathematics or quantitative methods and 2+ years of relevant work experience.
Credit risk management industry experience in developing scoring models will be a strong plus for this position. Identity Fraud industry experience is a strong plus also
Experience working with Big Data Technologies and applying large scale machine learning techniques within these technologies
Demonstrated ability to apply modern data exploration and visualization techniques to deliver actionable insights.
Experience with Unix/Linux system architecture and command line tools
Experience developing tools to aid in data science endeavors
RSA is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at Dell are based on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. Dell will not tolerate discrimination or harassment based on any of these characteristics. Dell encourages applicants of all ages. Read the full Equal Employment Opportunity Policy here.