Duties/Responsibilities:  
The RDMO Offense Data SME will drive the initiatives on the data offense value creation strategy.  
The SME will be responsible for project management, business and data analysis of the following:
•    Identifying and documenting tasks, milestones, and timeline for individual initiatives
•    Partnering with internal business resources to develop requirements and success factors
•    Define KPIs
•    Ensure the appropriate use of NLP/AI/ML where the opportunity exists
•    Partnering with internal and external technology resources to develop and monitor implementation plans
•    Communication on progress of plan to Stakeholders and management
•    Supporting vendors, technology and business partners with the various tasks
•    Identifying and remediating risk and issues and escalations to management 
•    Assigning and tracking dependencies, resources and progress
•    Data analysis
•    Perform analysis and provide recommendation for solution analysis, design and implementation
•    Evaluate alternatives and present the most efficient and cost-effective solution
•    Testing deliverables to ensure requirements are met
•    Coordinate delivery and adoption planning
•    Monitor implementation and delivery plans, manage roadblocks and escalations
•    Provide estimates on cost, impact and feasibility of proposed solutions
•    Provide training materials and training for new solutions
•    Provide end user support of deliverables
•    Track impact of solutions, measure sand report via KPIs

PROFILE REQUIRED

MINIMUM REQUIREMENTS:

EDUCATION: Bachelors degree in Computer Science, Computer Engineering, Data Science, Math, Finance, Economics, or related field required; Masters degree preferred

EXPERIENCE: 3-7 years of related experience preferred

SKILLS AND EXPERIENCE NEEDED:

Description of the skills/knowledge/expertise required:
•    Knowledge of Financial Services, Investment Banking preferred, with strong focus on data management, governance and quality
•    Knowledge of Data Management and Governance 
•    Knowledge of AI/ML in the financial industry
•    Knowledge of NLP in the financial industry
•    Knowledge of delivery of AI/ML solutions delivering efficiencies, insights and/or revenue
•    Knowledge of Data Ops supporting AI/ML implementations
•    Knowledge of working in a technical role in the financial industry
•    Knowledge of experience working with vendor technology solutions in the financial industry
•    Strong expertise in building application solutions, R, Python, Java, …
•    Hands on data access via SQL, Hadoop, Hive, Avro, and/or other data storage solutions
•    Strong understanding of system design and architecture concepts including DaaS, Data Virtualization and Data Distribution
•    Ability to define technical specifications based on client business requirements or functional specifications from business analysts
•    Strong analytical and debugging skills