Description:
Data Scientist and MI communities, many of whom we collaborate with closely. The team is also responsible for regulating the data environment, including platform architecture, management and configuration, security and data quality.
In This Role, You Will
- Uses a range of data tools (including SQL and python on Hadoop and GCP environments) to perform analysis/analytics tasks on a broad range of dataset to yield insight which informs design of business and technical processes and data assets.
- Demonstrates traceability of functional and non-functional requirements and solution design.
- Create analysis of data-driven product functionality.
- Provides insight as to how a Data Analyst should learn and progress throughout the organisation.
- Drives adoption of the practice across the Data Analyst community.
- Works with stakeholders, engineers and senior team members to define the problem statements, questions and requirements that the role holder and team will deliver
- Manages and evaluates the change impact assessments of proposed requirements.
- Understands and challenges the implications of change such as dependencies, feasibility, scope, outputs, and process.
- Manages and provides domain expertise to support design development activities; e.g. reviewing technical documentation and working with data and technical specialists from stakeholder teams to design their capabilities (including models and business processes)
- Manages and helps prepare for Design Authorities and other forums and works with the development team to ensure challenges raised are addressed.
- Manages, tracks and reports delivery progress against requirements.
- Works with the Product Owner to manage, define and track performance measures. Supports and guides the Product Owner to create/evolve Product roadmap, creation of epics and writing of user stories and managing the product backlog.
- Helping define and track metrics and Key Performance Indicators for the product.
- Drive the Agile Team performance and outcome metrics as required, building and using their expertise in Agile.
To be successful in this role you should have the following skills:
- Knowledge and experience analysing large and complex datasets to yield actionable technical and business insight.
- Experience with Hadoop and/or Cloud Technologies (ideally GCP) and a willingness to build knowledge in these areas quickly.
- Fluency in SQL for data analysis/analytics with experience designing more advanced queries.
- Expertise in python or other scripting languages for the purpose of advanced analytics. Building python expertise (or alternative languages in future) for data science/analytics purposes is a requirement of the role.
- Working knowledge and familiarity with financial services organisations and typical customer products
- Familiarity with data security, privacy and access considerations when dealing with sensitive data from multiple jurisdictions
- Previous experience working in a financial (or wider) crime domain desirable
- Comfortable directing their work and priorities to delivery within appropriate timeframes based on a moderate level of guidance and direction from their manager and team leadership
- Communicates priorities and requirements effectively to other teams and team members to ensure capabilities are built in alignment with expectations
- Support and mentoring to junior analysts within the team
- Ability to understand complex and unfamiliar problems within the role domain with a broad range of business and technical constraints and dependencies, designing data driven solutions to address them
- Proactively building expertise in new tooling, concepts, industry trends and programming languages relevant to the role within anti-financial crime, data science, AI and financial services
- Ability to build understanding on domain topics around data and financial crime to solve problems in a rapidly changing landscape and build a working technical knowledge where needed
- The role holder will be responsible for design decisions relating to their data design and analytics projects or capabilities that they own within the team