Specialist - Data Management Job in The Bank Of New York Mellon Corporation

We are seeking to build a cadre of Data Engineers who will support a wide range of Data Science initiatives and manage a very large data pipeline within the BNYM data lake and cloud infrastructure. This team will ingest, parse, extract content and metadata, correlate, disambiguate, integrate, analyze, tag and build large ingestion pipelines into BNYM cloud-based and on-premises data libraries/lakes.

They will build production implementations of data pipelines that support production AI/ML models.

Primary candidate qualification is Aptitude and Attitude, with a demonstrated history of on-the-job learning to quickly master necessary skills.

Range of Levels:

• 3 - Feature Engineers (I): Curates and processes data resources in support of data science analytics. Leverages software engineering and infrastructure resources to build data products and pipelines. Responsible for data reception, parsing, validation, ingestion, and pipeline processing in partnership data management organizations, and functional and subject matter experts to deliver value.

• 2 - Senior Feature Engineers (J): Defines, develops, maintains and delivers strategic data pipelines and products that provide value, including entity extraction, correlation and master data resources. Responsible for assigned data pipeline from reception to delivery including integration with master data systems as appropriate. May allocate/coordinate work within a team/project.

• 1 - Lead Feature Engineer (K): Defines, develops, maintains and delivers complex strategic data products that demonstrate value. Leverages simple to advanced data techniques to support, integrate, and cross-correlate multiple and complex data pipelines. Responsible for multiple data pipelines from reception to delivery. Responsible for effective integration with master data systems and data. Partners with functional and subject matter experts to deliver value.

JOB DESCRIPTION

Data Engineer - Supports the research, experimentation, implementation, and metrics of multiple machine learning, applied algorithms and artificial intelligence implementations aimed at innovative and transformative solutions in a highly complex, enterprise- scale context.

Assesses business viability of new approaches, models, and related technologies. Consults with other senior level IT managers to plan, assess, evaluate and transform current strategies. Supports a cross-LOB business data science practice, with an initial focus on aggregating information and metadata resources, feature engineering, current AI/ML prototypes and emerging programs to drive enterprise-wide commercially significant insights and risk-based analyses related to the overall (cross-LOB) application portfolio.

Prepares and delivers presentations to top-level management on new technology and its impact on the organization. Leads strategic direction of other data Engineers throughout the enterprise. Stays abreast of the science, methods, practices, approaches and research in the industry and marketplace. Uses expertise to develop or refine innovative, creative approaches to solve client challenges. Advanced degree in computer science and/or related disciplines.

3 to 12+ years of experience in computer science and/or related disciplines, with demonstrated experience supporting AI/ML. The preferred candidate will have experience in the application of AI/ML in the financial context.

Essential Data Science Skills:

• Python, Jupytr, SQL, NoSQL

• Bachelor's degree in computer science or a related discipline, or equivalent work experience required.

• Experience working with large relational databases (MS SQL Server, Oracle, Vertica, GCP/Azure/AWS DB services).

• Must have strong analytical and problem-solving skills and quickly learn new application systems and technology.

• Experience with working with structured and unstructured data and determining predictive significance.

• Experience with defining, designing and deploying to supported production systems for data pipelining for Machine Learning applications.

• Experience with processing unstructured data; natural language processing (NLP), classifying, categorization.

• Experience with big data ingestion and transformation.

• Experience with the metadata and techniques required for identifying, tracking (pedigree/lineage), confidence, provenance and security of datasets, files and objects.

• Experience in the securities or financial services industry is a plus.

• Experience with the Agile methodology and working in geographically dispersed teams.

• Excellent collaboration and communication skills (oral, written)

Desired Data Science Skills: Some combination of: Natural Language Processing (NLP), Time-Series, Econometrics, Deep Learning, Neural Nets, Power BI, Tableau, Cloud (GCP or Azure), Spark, Java, Big Data.

Essential Software Project Skills:

Jira, GIT, Confluence/Wiki, MS Office (MS Word, MS Excel, MS PowerPoint).

Qualifications

Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required, 6-12 years of experience in software development required, experience in the securities or financial services industry is a plus, should have thorough knowledge of the software development cycle.