In Antal we have been dealing with recruitment for over 20 years. Thanks to the fact that we operate in 10 specialised divisions, we have an excellent orientation in current industry trends. We precisely determine the specific nature of the job, classifying key skills and necessary qualifications. Our mission is not only to find a candidate whose competences fit the requirements of the given job advertisement, but first and foremost a position which meets the candidate’s expectations. Employment agency registration number: 496.
Model Owner
In today’s digital world, the company needs to continuously develop innovative ways of customer interaction with our products and services. We are building new technology and enhancing our existing systems and offerings, to allow us to maximise the benefits of the latest technological advancements and trends.
This role will be within the Digital Identity Sub-Value Stream (DI SVS). DI SVS is focused on identifying and working with some of the most interesting external vendors from around the world to provide cutting edge products to the wider bank and our more than 40 million global customers.
One of our most strategic products is a global digital identity validation & authentication service that provides any market with the ability to verify a person’s identity, via an API integration. We partner with a selection of third-party vendors to deliver real time identity and anti-impersonation checks as part of a digital journey.
Our product enables customer to capture their government issued identity document (including passport, driver’s license, national ID card) and verifies the document’s authenticity. This is then combined with fully digital anti-impersonation check.
Our identity verification service is now live across multiple markets and available to customers across multiple journeys. There is a deep product roadmap which includes extensive data-driven optimisation of the product, creating new features, boosting the overall effectiveness of the platform and to deploying the solution across multiple bank's markets.
The Role
The Model Owner focus on the documentation, assessment, deployment, monitoring and maintenance of machine learning and AI models.
The model owner will work with internal and external stakeholders to ensure model comply with internal as well as external polices related to the use of machine learning and AI models. Document the models to confirm to the bank polices for implementation of machine learning and AI models, these include references of reference for new models, implementation report detailing the mechanisms of the model.
The model owner will need to assess and test 3rd party models to determine their suitability for use within the bank, talking into considering on how the model was developed and tested.
The model owner will determine the risk of implementation of the model taking into factors like country risk appetite & exposure of the models and ensure the consumes of the model agree with the risk.
Collaboration with delivery teams in the development and implementation of the models and taking responsibility for the communication of delivery to model stakeholders.
Monitoring all live models ensuring the model operates to agreed performance and ensuring they operate accordingly to the bias thresholders defined.
When the model is not operating as expected help to identity the issue, propose solutions and be able to verify any corrections or updates to the model.
The role will ideally suit motivated self-starters, who are able to communicate easily across a broad cross section of people from around the world, who are able to collaborate closely with a crossfunctional, truly agile team. The Model Owner will be an SME and will have a huge impact on the scale and success of the whole initiative. Finally, the model owner will also support the head of delivery for all data model governance activities.
Responsibilities:
- Collaborate with data scientists, engineers, and stakeholders to define project requirements and deliverables
- Define and maintain model development best practices and standards
- Evaluate and select appropriate algorithms and techniques for various machine learning applications
- Perform data exploration and analysis to identify relevant features and patterns
- Conduct model performance evaluation and optimization to ensure accuracy and efficiency
- Develop and maintain model deployment and monitoring pipelines
- Identify and mitigate potential model bias or ethical concerns
- Provide training and documentation to end-users and stakeholders
- Keep up-to-date with the latest advancements in machine learning and data science
Knowledge & Experience / Qualifications
- Bachelor's or Master's degree in computer science, data science, or a related field
- Solid understanding of statistical analysis and data modeling concepts
- Experience with data visualization tools such as Tableau or PowerBI
- Programming skills in Python or R would be advantageous
- Excellent problem-solving and analytical skills
- Strong communication and collaboration skills
- Ability to work in a fast-paced and dynamic environment
What we offer:
- Very friendly agile team with high amounts of autonomy, delivery team including PO and SM locally, senior project stakeholders in UK, internal customers from all over the world
- Very rare possibility of building new features, starting from the discovery phase but with lots of product and customer understanding available (the product is already live in several markets)
- Guarantee that solution built will be widely used and globally recognized, hopefully making customers happy by simplifying their interaction with the bank
- Personal development and growth opportunities within the company
- Ability to work in an environment where quality is prized over quantity – where it is understood that technical excellence pays off
- Unprecedented learning opportunity in pure serverless AWS environment from experts inside the team
- Ability to work on advanced machine learning and AI techniques and tools
