Data Scientist SQL, Python, Banking or Capital Markets
Job Summary
Job Description: 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
5 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
Bachelors degree required; experienced candidates prioritized
Best vs. Average Candidate
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
Required Skills:
Experience (Years): 8-10