Senior Data Product Management Consultant

About this role:

Wells Fargo is seeking a Senior Data Product Management Consultant.

In this role, you will:

• Lead or participate in moderately complex data product initiatives and deliverables and contribute to large-scale planning related to driving data enablement and capabilities across multiple platforms and utilities
• Review and analyze moderately complex data product challenges that require an in-depth evaluation of variable factors to drive data enablement strategies and roadmaps
• Independently resolve moderately complex data product issues and lead team to meet data product deliverables while leveraging solid understanding of data, analytics, and integration needs of line of business partners that impact prioritization, roadmap, and architecture design
• Collaborate and consult with peers, colleagues, and mid-level managers to ensure data product solutions are built for optimal performance and design analytics applications across multiple platforms, resolve data product issues, and achieve goals; may lead projects, teams or serve as a mentor for lower-level staff
• Provide input on new use case intake, prioritization, product roadmap definition, and other critical business processes
• Manage moderately complex datasets continuously focusing on the consumers of the data and their business needs, while adhering to set data governance and standards
• Create and maintain data product roadmaps and documentation throughout the data product life cycle with detailed specifications, requirements, and flows for data capabilities
• Serve as a liaison between data management, product teams, data engineering, and architecture teams throughout the data product life cycle

• 4+ years of data product or data management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Key Responsibilities:

• Collaborate with business stakeholders to gather and refine requirements for data use cases.
• Design and architect scalable data models and data element relationships with a strong emphasis on usability, performance, and data accuracy.
• Identify and write requirements for data source integrity monitoring.
• Support database enhancement requests and contribute to logical data design solutions.
• Experience of working on end-to-end data science pipeline with the ability to clearly design efficient data models, training data samples, training pipelines and inference pipelines to ensure reproducibility.
• Strong experience in evaluating different types of AI/ML outputs and models (recommender systems, similarity scoring, classification and regression).
• Should be able to break down complex business problems into sub-tasks that can be solved with AI/ML to enable decision making on a scale. Should have good grasp on statistical concepts and empirical methods that drive post-modelling decisions like sorting, ranking, selection etc.
• Should have good experience in converting POCs and experimented models into production grade AIML systems, have the ability to collaborate effectively with ML engineering and MLOPs teams to take AI/ML models to production, build and serve models through APIs and support integration of AI/ML models into web-aps.

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• Plan project tracks around AI/ML and data science and balance delegation and hands-on development.
• Experience in taking first principles approach to solving data science problems, understand and communicate data requirements to data engineering teams and explain model outputs to business users.
• Ability and experience in engaging business users to understand requirements and translate them into technical data science problems. Be exceptional at communicating and translating model algorithms and their outputs to non-technical users and stakeholders.
• Fluent in agile ways of working and agile project management practices. Should be comfortable to create efficient user stories, and other agile project artifacts.

Required Skills:

• Data Analysis: Experience in data cleansing, validation, and transformation logic using Alteryx and SSMS.
• Proficiency in Python programming with hands-on experience in developing and debugging code.
• Data Science(Modelling, ML, Statistical forecast.
• MSSQL: Ability to write, read, and optimize queries for data extraction, transformation, and analysis.
• Experience with Google Data Cloud stack (Dataplex, big query, etc.).
• Experience with metadata management and data governance practices.
• Proficiency in data profiling and root cause analysis for data quality issues.
• Familiarity with Agile processes and Atlassian software (Jira).