BNY Mellon 2022 SETUP Technology Full Time Program - Data Scientist in New York, New York
Software Engineering & Technology University Program (S.E.T.U.P) The Software Engineering & Technology University Program (S.E.T.U.P) is a pipeline to recruit, develop, and retain high-potential entry-level technology professionals who are prepared and positioned to contribute to the successful execution of BNY Mellon's technology strategy and initiatives. The 2022 S.E.T.U.P program will begin in Summer 2022. Program At A Glance: Assignments across various job functions within Technology\* that combine learning with skill development through practical work and projects; Extensive training curriculum and ongoing learning assignments that will help develop technical, professional, interpersonal and leadership skills; and Career development and networking support from a host of corporate leaders including executive mentors, peer mentors, business stakeholders and a dedicated program manager. Upon successful completion of the program and based on overall business need, S.E.T.U.P participants will be matched to a full-time role, taking into account factors such as business requirements, analyst preferences, and overall performance throughout the program. Program Locations: US: Pittsburgh, PA \*New York, NY \* Jersey City, NJ Program Highlights: Small, selective program size that allows for more personal attention and support; Participants can further develop technical skills/expertise, enhance leadership abilities, build networks across the organization and accelerate their careers; Robust onboarding and training curriculum designed specifically for S.E.T.U.P participants; Visibility and exposure to senior leaders in small cohorts and/or one-to-one meetings; Full commitment from top-level management to make our program the premier technology talent pipeline program within the financial services industry Data Scientist Primary Responsibilities: Participate on a team to apply scientific method to find solutions to real business problems. Perform data analysis, feature engineering and advanced methods to prepare and develop decisions from data. Leverage simple to advanced data techniques to support the team to deliver data analytic products for the firm. Performs analytics in support of the identification and understanding observed business outcomes. Collaborates with others to deliver on hypothesis testing and developing the mathematics to describe the business opportunity. Communicates effectively with analytics staff. Develops analytics, prepares and delivers both informational and decision-seeking presentations. Stays abreast of organization and management changes and has in-depth knowledge of company practices relevant to data science products. Maintains knowledge of company's total computing environment and planned changes in order to develop meaningful data science products. Grow and develop skills across the 3 domain specialties: Machine Learning, Feature Engineering and Advanced Analytics capabilities. Stressing expertise in the core functional areas: Computer Programming, Math&Analytic Methodology, Distributed computing and communications of complex results. Qualifications Program Eligibility/Qualifications: Bachelor's degree required. Candidate is typically a recent college hire with a bachelor's degree in computer science engineering or a related discipline. 0-3 years of experience in software development preferred. Previous technology internship is a plus Our ambition is to build the best global team - one that is representative and inclusive of the diverse talent, clients and communities we work with and serve - and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums. Primary Location: United States-New York-New York Internal Jobcode: 96003 Job: Information Technology Organization: Campus Development Program-HR12545 Requisition Number: 2116931
BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer.
Minorities/Females/Individuals With Disabilities/Protected Veterans.