Data Scientist - SQL, Python, Banking or Capital Markets

Job Title

Data Scientist

Duration

12 Months

Work Model

Hybrid (3 days per week in office)

Role Overview

We are seeking an experienced Data Scientist with strong Banking and Capital Markets domain expertise to support data-driven decision-making initiatives. The role focuses on analyzing complex financial datasets, developing statistical and machine learning models, and supporting risk, compliance, and regulatory use cases. The ideal candidate brings deep analytical skills, strong SQL and Python experience, and the ability to translate business and regulatory requirements into effective analytical solutions.

Typical Day in the Role

• Analyze large, complex datasets from banking and capital markets domains to extract insights and identify trends
• Develop, validate, and deploy statistical models and machine learning solutions to support business initiatives
• Collaborate with business stakeholders to translate financial and regulatory requirements into analytical solutions
• Support risk, compliance, and regulatory reporting use cases (e.g., stress testing, credit risk)
• Perform data exploration, feature engineering, and model performance evaluation
• Design and optimize SQL queries for data extraction, transformation, and analysis
• Develop analytics workflows and models using Python and related libraries
• Communicate insights through dashboards, visualizations, and clear documentation
• Ensure data quality, integrity, and compliance with internal governance and regulatory standards

Candidate Requirements

Must-Have Skills

• 10+ years of proven experience as a Data Scientist or Data Analyst, with 10+ at least 5 years in Banking or Capital Markets calculations
• 5+ years of proficiency in SQL for complex data querying and performance optimization
• 2+ years of hands‑on experience with Python (basic coding knowledge)
• Experience working with large structured and unstructured datasets
• Strong foundation in statistics, data analysis, and predictive modeling

Nice-to-Have Skills

• Strong understanding of financial products, markets, and industry data
• Knowledge of regulatory frameworks and reporting
• Familiarity with data visualization tools such as Power BI or Tableau
• Basic understanding of LLMs and AI tools (e.g., Copilot)

Soft Skills

• Strong analytical thinking and problem-solving abilities
• Excellent communication and stakeholder management skills
• Ability to work independently and collaborate effectively in cross‑functional teams
• High attention to detail with a strong focus on data accuracy and governance
• Ability to explain complex models and results to non‑technical audiences

Education

Bachelor’s degree required; experienced candidates prioritized

Candidate Profile

Best Candidate:

• Extensive experience in Banking and Capital Markets data analysis
• Strong regulatory and risk domain knowledge
• Hands‑on expertise in SQL and Python applied to real‑world financial use cases

Average Candidate:

• Solid data science fundamentals with some banking exposure
• Meets core SQL and Python requirements
• Limited regulatory or advanced financial domain experience