Transformation Data Lead, Markets -VP
Citi · Canada · 20d ago
Responsibilities:
- Support transformation programs and project decision-making by answering complex business questions through data.
- Partner with product owners, risk specialists, business experts, technology teams, and program stakeholders to define analytical questions, identify data requirements, and interpret results.
- Analyze complex data models using SQL and Python to answer business questions, assess data quality, identify relationships and anomalies, and evaluate potential solutions.
- Develop reusable frameworks and programmatic solutions for recurring and ad hoc data problems, including cross-system regression testing, data-quality validation, data-model analysis, and data-pipeline assessment.
- Rapidly develop proofs of concept and prototypes based on regulatory rule text, business interpretations, or emerging program requirements to clarify requirements, test assumptions, reduce uncertainty, and inform the development of longer-term data models, technology platforms, and production systems.
- Translate business and regulatory requirements into testable decision logic, algorithms, decision trees, data models, and prototype analytical solutions.
- Decompose complex business processes and real-world concepts into appropriate data structures, including normalized models, entities, attributes, relationships, and reference data.
- Contribute to the design and assessment of data pipelines, transformation logic, workflow dependencies, and enterprise-scale data environments.
- Identify activities for which agentic large language model solutions may be beneficial and design appropriate workflows to improve efficiency, automate suitable tasks, and reduce time to market for analytical results.
- Apply relevant quantitative financial analysis techniques, which may include backtesting, risk modeling, derivative pricing, Monte Carlo analysis, and scenario testing. Develop visualizations, diagrams, documentation, and knowledge-management artifacts that communicate complex findings clearly and remain maintainable over time.
- Communicate analytical approaches, assumptions, data limitations, risks, and results to business and technical stakeholders.
- Manage assigned work independently using tools such as Jira, Confluence, and GitHub to organize activities, document decisions, maintain analytical artifacts, and support collaboration.
- Handle sensitive, confidential, and controlled data in accordance with applicable access controls, data-governance requirements, and information-security standards.
- Appropriately assess risk when making business decisions, with particular consideration for Citi’s reputation and the safeguarding of Citigroup, its clients, and its assets. This includes complying with applicable laws, rules, regulations, and Citi policies; applying sound ethical judgment; and escalating, managing, and reporting control issues with transparency.
Recommended Qualifications:
- 5 to 10 years of relevant experience as a individual, data analyst, data engineer, quantitative analyst, or in a comparable analytical role.
- Experience within financial services, with an understanding of how data supports business processes, risk management, regulatory obligations, controls, or transformation programs.
- Strong proficiency in Python and SQL, including experience investigating complex datasets and developing reusable analytical solutions.
- Experience with Python data analysis libraries and frameworks such as Pandas, Polars, or DuckDB.
- Experience analyzing complex data models, assessing data quality, and translating business questions into structured analytical approaches.
- Ability to prototype algorithms, business rules, decision trees, and analytical models without relying on the development or ownership of production machine learning models.
- Experience designing or evaluating data models, including normalization, entities, attributes, relationships, and reference data.
- Understanding of enterprise-scale data systems and architectures, including data lakehouses, Hive partitions, relational tables, data streams, data pipelines, and directed acyclic graphs.
- -xperience working with sensitive, confidential, or controlled data and applying appropriate data-handling, access, governance, and documentation practices.
- Ability to communicate effectively in both business and technical terms and to translate between business requirements and technical implementation concepts.
- Strong analytical and problem-solving skills, with a disciplined, scientific, and evidence-based approach.
- Ability to work independently, manage competing priorities, and deliver effectively in an agile transformation environment.
- Ability to create clear, maintainable visualizations, diagrams, technical documentation, and knowledge-management artifacts.
- Familiarity with project management, collaboration, documentation, and source-control tools, including Jira, Confluence, and GitHub.
- Diligent and organized working style, with intellectual curiosity, adaptability, efficiency, and a strong commitment to analytical quality.
Education:
- Bachelor’s degree or equivalent experience in computer science, data science, engineering, mathematics, statistics, economics, quantitative finance, or a related analytical discipline.
- A master’s degree in a relevant discipline is preferred.
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Job Family Group:
Project and Program Management------------------------------------------------------
Job Family:
Program Management------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Primary Location Full Time Salary Range:
$111,600.00 - $161,600.00------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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This job opening is for an existing job vacancy.
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