Project Manager

Job Responsibilities
- Manage the Data infrastructure and pipeline.
- Create, build, and maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources.
- Deliver high-quality, production-ready data pipelines that bring and cleanse data from source systems.
- Implement processes/systems to monitor data quality, and drive optimization, testing and tooling to improve data quality.
- Support model development and deployment
- Liaise closely with relevant stakeholders to identify and assess suitability of data.
- Liaise with Business Analyst and ensure assembled data sets used for model build meet business requirements.
- 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.
- 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.
- Ensure the seamless deployment of new analytics solutions and models without breaking anything or creating unintended effects in the production pipeline.
- Enhancement, Support and Team Contributions.
- 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.
- Performs data analysis required to troubleshoot data related issues and support the resolution of raised data issues.
- 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
- Model Validation
- 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
- Prior experience working on large-scale analytics projects (eg. Data Lake)
- Comfortable working with structured and unstructured data and distributed databases.|
- Familiar with best practice development and validation standards
- Basic understanding and knowledge of banking, risk management, regulatory recommendations and industry standards related to AML/AFC/compliance risks.
- Experience in or familiarity with analytics related to AML/AFC/Compliance risks are advantages.
- Ability to clearly communicate complex results in an easy-to-understand manner and tailoring them to different audiences.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- R and / or Python, with practical knowledge of data wrangling and machine learning libraries (e.g., Pandas, Keras, Tensorflow, Sklearn)
- Experience in data engineering tools, schema design, dimensional data modelling, robotic process, natural language processing and network link analysis
- Ability to create and maintain production ready data pipeline and deployment pipeline.
- Strong people skills and the ability to take a big picture approach to planning.
- 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