We are looking for a highly skilled Data Scientist to join the Machine Learning Model Development & Integration program within Financial Crime Technology.
In this role, you will design, develop, and optimise machine learning models that enhance detection accuracy across Anti Money Laundering (AML), Fraud, Transaction Monitoring, and Customer Behaviour Analytics.
You will collaborate closely with Data Engineers, ML Engineers, SMEs, and Product teams to build models that are accurate, explainable, performant, and compliant with regulatory standards such as PRA SS2/21.
Skills & Experience Required-
Technical Skills
• Strong proficiency in Python, ML libraries (scikit-learn, XGBoost, PyTorch/TensorFlow), and statistical modelling.
• Experience building and evaluating models for structured and unstructured data.
• Hands-on familiarity with cloud ML platforms (preferably AWS SageMaker).
• Strong foundations in statistics, probability, and algorithmic understanding.
• Experience with MLOps tools such as MLflow, Weights & Biases, or SageMaker Pipelines (desirable).
• SQL expertise and comfort working with large datasets.
Domain/Platform Skills
• Knowledge of financial crime, AML typologies, KYC, sanctions, or fraud analytics (preferred but not mandatory).
• Understanding of model risk, explainability, fairness, data drift, and model monitoring frameworks.
Soft Skills
• Ability to translate complex technical results into actionable business insights.
Responsibilities
We are looking for a highly skilled Data Scientist to join the Machine Learning Model Development & Integration program within Financial Crime Technology.
In this role, you will design, develop, and optimise machine learning models that enhance detection accuracy across Anti Money Laundering (AML), Fraud, Transaction Monitoring, and Customer Behaviour Analytics.
You will collaborate closely with Data Engineers, ML Engineers, SMEs, and Product teams to build models that are accurate, explainable, performant, and compliant with regulatory standards such as PRA SS2/21.
Skills & Experience Required-
Technical Skills
• Strong proficiency in Python, ML libraries (scikit-learn, XGBoost, PyTorch/TensorFlow), and statistical modelling.
• Experience building and evaluating models for structured and unstructured data.
• Hands-on familiarity with cloud ML platforms (preferably AWS SageMaker).
• Strong foundations in statistics, probability, and algorithmic understanding.
• Experience with MLOps tools such as MLflow, Weights & Biases, or SageMaker Pipelines (desirable).
• SQL expertise and comfort working with large datasets.
Domain/Platform Skills
• Knowledge of financial crime, AML typologies, KYC, sanctions, or fraud analytics (preferred but not mandatory).
• Understanding of model risk, explainability, fairness, data drift, and model monitoring frameworks.
Soft Skills
• Ability to translate complex technical results into actionable business insights.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Technical skills-
5–8 years as an SDET/QA Engineer focusing on Python for non‑GUI testing of APIs/services and data workflows.
Strong SQL and data concepts (ETL/ELT, partitioning, schema evolution).
Hands‑on with Jira and Agile practices (Scrum/Kanban).
Git proficiency and GitLab CI awareness (pipelines, runners, artifacts).
Cloud testing/automation experience on AWS and/or GCP.
Nice‑to‑have / Advantage:
Data pipeline testing with Airflow/dbt/Spark/Beam/Kafka.
Data quality tooling (e.g., Great Expectations, Deequ) or equivalent custom checks.
Responsibilities
Technical skills-
5–8 years as an SDET/QA Engineer focusing on Python for non‑GUI testing of APIs/services and data workflows.
Strong SQL and data concepts (ETL/ELT, partitioning, schema evolution).
Hands‑on with Jira and Agile practices (Scrum/Kanban).
Git proficiency and GitLab CI awareness (pipelines, runners, artifacts).
Cloud testing/automation experience on AWS and/or GCP.
Nice‑to‑have / Advantage:
Data pipeline testing with Airflow/dbt/Spark/Beam/Kafka.
Data quality tooling (e.g., Great Expectations, Deequ) or equivalent custom checks.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Role Category :Programming & Design
Role :Quality Automation specialists - Java| Python Selenium| Automation frameworks| AWS cloud working experience
Network Design & Delivery
· Lead end-to-end delivery of enterprise network projects covering LAN, Wireless, and SD-WAN technologies.
· Perform network scoping, solution design, and implementation aligned with approved architecture standards.
· Create and review HLDs, LLDs, BOMs & Runbooks, implementation plans, and handover documentation.
· Drive Network Refresh, EOL/EOS remediation, and technology modernization initiatives.
· Ensure solutions meet performance, scalability, resiliency, standard and security requirements.
LAN & Wireless Engineering
· Deliver enterprise campus LAN solutions using Cisco (Catalyst or Meraki) switching platforms.
· Design and implement Enterprise wireless networks including Wi-Fi 5/6/6E, high-density environments, and site readiness.
· Working knowledge with NAC solutions (Cisco ISE) for wired and wireless access control.
· Support wired/wireless troubleshooting during deployment and stabilization phases.
SD-WAN & Secure Connectivity (Good to have/Working knowledge)
· Design and implement SD-WAN solutions.
· Collaborate with security teams on secure connectivity patterns, firewall integration, and segmentation.
Automation & Quality Improvement
· Contribute to network automation and standardization efforts (Ansible, templates, APIs, or vendor tools).
· Identify delivery inefficiencies and drive process, quality, and documentation improvements.
· Participate in design reviews, quality checks, and peer mentoring.
Stakeholder & Vendor Engagement
· Work directly with internal customers, project managers, and global stakeholders.
· Coordinate with OEMs, ISPs, and system integrators for implementation and issue resolution.
· Provide clear communication on project status, risks, and dependencies.
Responsibilities
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
