Project Manager
· Job Responsibilities
o Manage the Data infrastructure and pipeline.
o Create, build, and maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources.
o Deliver high-quality, production-ready data pipelines that bring and cleanse data from source systems.
o Implement processes/systems to monitor data quality, and drive optimization, testing and tooling to improve data quality.
o Support model development and deployment
o Liaise closely with relevant stakeholders to identify and assess suitability of data.
o Liaise with Business Analyst and ensure assembled data sets used for model build meet business requirements.
o Support Data Scientists in developing model narratives by providing inputs from a data perspective; and in ongoing testing of models/outputs during development, prior to more formal model validation by an independent team.
o Create a model deployment pipeline to automate deployment of models in client environments/systems and work closely with Data Scientists) in the Modelling team and other stakeholders to ensure models are production ready.
o Ensure the seamless deployment of new analytics solutions and models without breaking anything or creating unintended effects in the production pipeline.
o Enhancement, Support and Team Contributions.
o Identify, design, and implement enhancements for internal process related to data (e.g., optimizing data delivery, re-designing infrastructure for greater scalability) to improve data reliability, efficiency, and quality.
o Performs data analysis required to troubleshoot data related issues and support the resolution of raised data issues.
o Support the validation team lead in defining and maintaining minimum standards of model performance, applicable at the time of model development and upheld via subsequent validation exercises
o Model Validation
o Conduct independent validation of AML models as per the standards defined by the validation team, and document all findings in a comprehensive report, along with recommended areas of attention (to bridge any gaps identified).
· Job Requirements
o The role is expected to have 5 - 7 years of experience working in technology and/or data analytics space, preferably 2 - 3 years of experience working in with advanced analytical models/tools/applications (e.g., machine learning, data-lake) in banking areas.
o Prior experience working on large-scale analytics projects (eg. Data Lake)
o Comfortable working with structured and unstructured data and distributed databases.|
o Familiar with best practice development and validation standards
o Basic understanding and knowledge of banking, risk management, regulatory recommendations and industry standards related to AML/AFC/compliance risks.
o Experience in or familiarity with analytics related to AML/AFC/Compliance risks are advantages.
o Ability to clearly communicate complex results in an easy-to-understand manner and tailoring them to different audiences.
o Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
o R and / or Python, with practical knowledge of data wrangling and machine learning libraries (e.g., Pandas, Keras, Tensorflow, Sklearn)
o Experience in data engineering tools, schema design, dimensional data modelling, robotic process, natural language processing and network link analysis
o Ability to create and maintain production ready data pipeline and deployment pipeline.
o Strong people skills and the ability to take a big picture approach to planning.
o Strong communication skills to interact with data scientists, business end-users, and possibly external vendors to design and develop data solutions.
Job Type: Contract
Contract length: 12 months
Pay: $9,000.00 - $12,000.00 per month
Benefits:
- Health insurance
Schedule:
- Day shift
Work Location: In person