Senior AI/ML Data Management Specialist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Enterprise Analytics and Data Science (EADS) is seeking a Senior AI/ML Data Management Specialist within the Artificial Intelligence Machine Learning Center of Excellence.

The Artificial Intelligence Machine Learning Center of Excellence (AI/ML CoE) is responsible for the design, development, and maintenance of AI models at Wells Fargo. The AI/ML CoE is seeking a dynamic professional that has a strong background in Data management processes and policies in the banking domain and also a good understanding of AI/ML solutions, processes, platforms and tech stack. The selected candidate will lead several foundational work streams, including critical work related to the implementation and measurement of initiatives supporting key process and governance priorities that span risk domains, with an initial focus on data and technology risk Successful candidates will be self-motivated, nimble, and have a strong bias for action. This position will become a subject matter expert with respect to operational process excellence across the CoE, and will work closely with CoE leadership.

Make sure the level match…is your posting also for a lead business execution consultant?

In this role, you will:

• Facilitate the design and improvement of key operational processes and control frameworks that span domains such as data management, data hygiene and code use lifecycle
• Partner across CoE (Data science, Platforms and Engineering teams) and also with technology teams to design and execute initiatives that will result in more efficient process execution while managing risk and improving quality
• Partner with Data Management Solution group to understand data governance, data quality and metadata policies, standards, tools, processes or procedures to ensure data control and remediation for gaps in AI/ML processes and clusters
• Combine data management policy knowledge along with technical acumen across AI/ML modeling, platform and engineering to suggest and implement best in class solutions
• Drive the creation and documentation of group inputs to enterprise risk and control initiatives
• Interface with oversight stakeholders including model risk management, Internal Audit, independent risk management

Required Qualifications:

• 6+ years of Data Management, Data architecture, Product Management, Consulting, or Business Operations experience, or equivalent
• S. / B.E. / B.Tech in quantitative disciplines like operations research, statistics, economics, econometrics, computer sciences, engineering, AI/ML
• Preferred : MBA from renowned business schools or Masters degree in business disciplines on top of Bachelors in quantitative fields
• Strong risk management and compliance skills from a data viewpoint, preferably in the banking domain
• Knowledge and understanding of data governance challenges and approaches: metadata, data quality, and data stewardship
• Knowledge of AI/ML and analytics processes and products, engineering capabilities, data clusters, data lake, data warehouse
• Ability and acumen to handle technical aspects like storage and compute, data cluster resource management, model training/deployment/scoring processes along with governance and compliance aspects

Desired Qualifications:

• Top candidate would have worked on one of these Data Science Platforms: Domino Data Labs, Databricks, H2O.ai, Datakitchen, Dataiku, Datarobot Kubeflow.
• Technical software/platform experience in the field of data driven products or data engineering pipelines is a plus
• Data management experience in a similar banking environment along with technical understanding of data platforms and systems will be highly desirable

Job Expectations:

• As mentioned above