At Discover, be part of a culture where diversity, teamwork and collaboration reign. Join a company that is just as employee-focused as it is on its customers and is consistently awarded for both. We’re all about people, and our employees are why Discover is a great place to work. Be the reason we help millions of consumers build a brighter financial future and achieve yours along the way with a rewarding career.
This position has full cycle accountability including designing and executing BAU and ad-hoc requests, conducting statistical, business and operation analysis to facilitate business decision-making The primary responsibility of this position includes ascertaining requirements, establishing valid data extraction specifications, designing project plans, extrapolating and manipulating information from internal and external data sources, and presenting results.
Responsible for applying machine learning and data science to develop quantitative capabilities for various needs across the organization. Explores new and innovative tools and technologies. Supports the organization’s transition to adoption of big data and cloud tools and technologies.
- Analyzes and mines large quantities of data to find patterns and insights. Utilizes open-source analytical stacks such as R, Python, Spark, etc.
- Develops and implements quantitative solutions that leverage structured and unstructured data from internal and external sources.
- Partners with technology teams to implement the quantitative solutions such as Hadoop, AWS, and Cloud-based ecosystems.
- Explores new tools and techniques available and ensures the organization remains on the frontier of analytic capabilities
- Utilizes machine learning and statistical algorithms to create data-driven solutions for various business applications.
- esigns project and develops commands to extract and manipulate information from specified internal and/or external data sources, using designated programming (SAS), query or scripting language and software tools such as SQL.
- Perform in-depth analyses using tools such as R, SAS/SQL to transform data into valuable information for decision making using statistical and machine learning techniques.
- Interprets results and prepares information in standard formats for presentation.
- Guides and assists business partners in marketing, finance and operations with routine statistical/modeling questions and issues.
- Takes on projects to perform ad hoc research and identify trends or developments that may impact business plans or performance or which may represent opportunities.
- Has in-depth statistical and business skills to understand key customer behaviors and financial drivers for deposit growth.
- Engages in continuous learning to maintain a high level of currency and competency in statistical and analytical principles, tools and techniques.
- Coordinates resources and interacts across functional boundaries as required to successfully complete project.
At a minimum, here’s what we need from you:
- Bachelor’s in Quantitative discipline (statistics, economics, engineering, computer science, or related field).
- In lieu of a degree, 1+ years of experience in data science.
- 1+ years of experience in prior data science internship in the industry
- Proven knowledge and expertise in statistical analyses
- Proficiency with statistical software and other analytical tools such as SQL, SAS, R, Python, SPARK, H2O, etc.
- Familiar with systems and data environments such as UNIX, Hadoop, AWS, Teradata, and Hive for data pulling, reporting, data manipulation, and segmentation analyses
- Demonstrated project management skills, including ability to prioritize, meet deadlines and follow through on completion of complex, high-profile projects
- Excellent communication and interpersonal skills, a team player and a self-starter with minimal direction
- Project management skills, problem solving skills and thought leadership
Discover Financial Services is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, among other things, or as a qualified individual with a disability.