Data Scientist

JOB SUMMARY / PURPOSE:

The AI Scientist will be instrumental in leveraging data to enhance the bank's AI conversation assistants and self-service digital channels. This role focuses on extracting, analyzing, and interpreting digital channel's and conversational data to provide actionable insights that drive process improvements, optimize customer journeys, and support evidence-based decision-making across various business units.

ROLE AND RESPONSIBILITIES:

• Data Collection & Management: Collect, validate, cleanse, and transform large datasets from various sources, including conversational platforms, and data warehouses, ensuring data accuracy and integrity.
• Data Ingestion: Ingest digital channels logs, anonymize/PII scrub, build vectorization pipelines, index maintenance, ETL for analytics and model monitoring data.
• BI & Reporting Development: Design, develop, and maintain reports, dashboards, and data visualizations (using tools like Power BI) to track Business KPIs, Conversation analytics, Model performance & quality, Infra & Operations and Compliance & audit reports
• NLU Performance Review: Review and analyse the Natural Language Understanding (NLU) performance of AI models to improve conversation flow and accuracy. Perform ad-hoc analyses to inform product priorities (e.g., identify content gaps, high-failure dialogs).
• Process Improvement: Identify opportunities for data process improvements, recommend system modifications, and automate reporting workflows to enhance efficiency.
• Stakeholder Collaboration: Work closely with cross-functional teams (e.g., AI Product Managers, AI Scientists and AI Engineers) to understand their data needs, gather reporting requirements, and provide analytical support.

PREFERRED SKILLS AND QUALIFICATIONS

• Education: Bachelor's degree in Computer Science, Data science, Statistics, mathematics, or a related field.
• Experience: Proven experience (3-5 years preferred) as AI Scientist, Data Analyst or BI & Reporting Analyst, ideally within the banking/financial services industry or working with AI products/digital journey design.
• Technical Skills:

-High proficiency in SQL Databases / data warehouse on-prem (Postgres, MongoDB, Oracle, SQL

server, Sybase)

-Expertise in BI and data visualization tools (e.g., Microsoft Power BI).

-Understanding of data warehousing, ETL processes, and database design concepts.

-Familiarity with statistical software or programming languages like Python for advanced

analytics.

-Familiarity with NLP models, LLMs and ML lifecycle (model versioning, inference tagging).

-Familiarity with ML observability tools (Grafana integration, MLflow metrics) and model

explainability tools.

-Familiarity with vector databases (Qdrant/FAISS/ Weaviate), retrieval metrics and conversational analytics tooling.

• Soft Skills:

-Strong analytical, problem-solving, and critical-thinking skills with keen attention to detail.

-Excellent written and verbal communication skills, with the ability to present complex information clearly to diverse audiences.

-Ability to work independently and collaboratively in a dynamic, fast-paced environment.

-Proactive mindset and intellectual curiosity about data and emerging AI technologies.