AI/ML Data Scientist

Barclays Capital; Gurugram District; Vor Ort; INR 1.800.000 - 3.200.000; Vollzeit

Zusammenfassung

Barclays is seeking an AI/ML Data Scientist to design, develop, implement and support mathematical, statistical, and ML models for business decision making. You'll collaborate with technology teams to define dependencies, build high quality analytics, and operationalise solutions across the organisation.

You will lead project work on predictive modeling, validation, monitoring, and deployment, contributing to scalable data products and performance tracking.

Qualifikationen

• Requires deep technical knowledge in analytics, ML, and modelling.
• Experience guiding analytics projects and collaborating with technology teams to operationalise models.
• Follows risk management and policy requirements for model development and deployment.

Aufgaben

• Design analytics and modelling solutions to complex business problems.
• Collaborate with technology to specify data, environments and tooling dependencies.

Kenntnisse

Python programming

ML & AI algorithms (NLP)

SQL

Spark/PySpark

Predictive modelling

Model lifecycle & governance

Jobbeschreibung

Purpose of the role

To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making

Accountabilities

• Design analytics and modelling solutions to complex business problems using domain expertise.
• Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
• Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
• Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
• Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users.
• Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
• Ensure all development activities are undertaken within the defined control environment.

Analyst Expectations

• To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
• Requires in-depth technical knowledge and experience in their assigned area of expertise
• Thorough understanding of the underlying principles and concepts within the area of expertise
• They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others.
• OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate.
• Will have an impact on the work of related teams within the area.
• Partner with other functions and business areas.
• Takes responsibility for end results of a team's operational processing and activities.
• Escalate breaches of policies / procedure appropriately.
• Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
• Advise and influence decision making within own area of expertise.
• Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
• Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
• Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Make evaluative judgements based on the analysis of factual information, paying attention to detail.
• Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
• Guide and persuade team members and communicate complex / sensitive information.
• Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.
• All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.

Step into the role of AI/ML Data Scientist at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences.

The Data Scientist position provides project specific leadership in building targeting solutions that integrate effectively into existing systems and processes while delivering strong and consistent performance.

Working with Applied AI Data Scientist role provides expertise in project design, predictive model development, validation, monitoring, tracking and implementation.

Key critical skills

• Strong proficiency in Python programming for data science and machine learning applications.
• Good understanding of Artificial Intelligence and Machine Learning algorithms, including Natural Language Processing (NLP).
• Strong working knowledge of SQL for data querying and manipulation.
• Hands-on experience with Spark/PySpark for processing and analysing large datasets.
• Experience in predictive model development, from model building through validation.
• Understanding of the model lifecycle and model management, including monitoring, govern