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AVP - Data Scientist & AI Engineer

Barclays

Pune

2-3 years

1 day ago

$20.5K–26.5K/yr

Full-time

Onsite

Skills Required LLM

RAG

LangChain

Gen AI

Prompt Engineering

Machine Learning

NLP

Python

SQL

Apache Spark

Databricks

XGBoost

PyTorch

Scikit-learn

LightGBM

Description The AVP — Data Analytics & AI is a hands-on technical leadership role within the Risk & Compliance division, responsible for designing, building, and deploying advanced analytics and AI solutions across risk domains. The role combines deep hands-on delivery with mentoring junior team members and contributing to the team's strategic roadmap.

Company: Barclays

Role: AVP — Data Analytics & AI

Location: Pune

Experience

- 2–3 years in financial services data analytics, data science, or AI/ML
- Experience within Risk, Compliance, or regulatory functions
- Proven track record of delivering production-grade ML models with measurable business impact
- Experience with model lifecycle including development, documentation, validation support, and monitoring
- Exposure to regulatory frameworks such as BCBS 239, Basel III/IV, or PRA/FCA guidance on AI/ML

Qualification

- Master's degree in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering, or related field
- PhD is a plus but not required
- Relevant certifications (e.g., AWS ML Specialty, Azure Data Scientist, FRM) are advantageous

Responsibilities

- Design, develop, and deploy ML models and data analytics solutions for credit risk, financial crime, operational risk, and compliance monitoring
- Build and maintain end-to-end ML pipelines from data ingestion to deployment
- Develop NLP and generative AI applications including document retrieval and regulatory analysis
- Deliver predictive analytics such as early warning models and anomaly detection
- Create and maintain BI dashboards and analytical reports
- Develop well-documented, reproducible models meeting internal Model Risk Management standards
- Prepare model documentation including methodology, validation reports, and monitoring plans
- Support regulatory exam preparedness and AI governance activities




- Maintain model inventories and performance monitoring frameworks
- Collaborate with Data Engineering and Cloud Platform teams for scalable data pipelines and data quality
- Work with cloud-native platforms and big data technologies for large-scale risk datasets
- Contribute to feature store development and data quality monitoring aligned with BCBS 239
- Partner with risk officers, compliance analysts, and business SMEs to translate requirements into analytical solutions
- Present model outputs and technical recommendations to senior stakeholders clearly
- Collaborate with cross-functional teams including Technology, Chief Data Office, and Front Office
- Mentor and guide junior data scientists and analytics engineers
- Conduct code reviews and knowledge-sharing sessions
- Contribute to hiring, onboarding, and technical competency development within the analytics team
- Stay current with emerging AI/ML research, tools, and techniques

Additional Responsibilities

- Advise and influence decision making and contribute to policy development
- Lead a team performing complex tasks and set objectives, coach employees, and appraise performance
- Demonstrate leadership behaviours to create an workplace for colleagues to thrive
- Lead collaborative assignments and guide team members through structured assignments
- Consult on complex issues and provide advice to support resolution of escalated issues
- Identify ways to mitigate risk and develop new policies/procedures for control and governance
- Take ownership for managing risk and strengthening controls
- Perform work requiring coordination with other areas to achieve organizational objectives
- Engage in complex data analysis from multiple internal and external sources
- Communicate complex or sensitive information effectively
- Influence or convince stakeholders to achieve outcomes




- Demonstrate Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship
- Demonstrate Barclays Mindset to Empower, Challenge, and Drive

Nice To Have

- PhD degree
- Certifications such as AWS ML Specialty, Azure Data Scientist, FRM
- Experience with Responsible AI practices including explainability and bias detection
- Knowledge of graph analytics or network analysis for financial crime detection
- Exposure to real-time streaming technologies like Kafka and Flink
- Experience with dbt, data quality frameworks, or metadata management tools
- Prior involvement in model validation reviews or regulatory examinations
- Experience with Agile/Scrum delivery methodologies
- Familiarity with emerging AI regulations (EU AI Act, UK AI regulatory framework)
- Published research or open-source contributions in ML or data science

More Skills Machine learning model development, Data analytics solutions, NLP and generative AI including LLM integration and RAG architectures, Power BI, Tableau, Big data technologies (Spark, Databricks), ML frameworks (scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow), Cloud platforms (AWS SageMaker, Azure ML), MLOps tooling (MLflow, Airflow), Kafka, Airflow, Snowflake, AWS S3, Azure, dbt, Git, Explainability tools (SHAP, LIME), AI governance frameworks (SS1/23, BCBS 239)

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