Transformation Program Management Lead, Markets -VP

Citibank (Switzerland) AG; Mississauga; Hybrid; Confidential; Full time

Job summary

Citibank (Switzerland) AG seeks a senior analytical professional to support transformation programs in Markets. The role applies data analysis, data engineering, and quantitative methods to translate regulatory and business requirements into practical solutions.

You will work with product owners, risk specialists, and technology teams to deliver high-quality analytical outputs for Citi’s Markets priorities.

Qualifications

• Bachelor’s degree or equivalent experience in a relevant analytical discipline; Master’s preferred.
• Strong proficiency in Python and SQL with ability to investigate complex datasets.
• Experience with Python data analysis libraries such as Pandas, Polars, or DuckDB.
• Experience translating business and regulatory requirements into structured analytical approaches.
• Experience designing data models, pipelines, and enterprise-scale data environments.

Responsibilities

• Answer complex business questions through data; define analytical questions and data requirements.
• Analyze complex data models using SQL and Python to assess quality and relations.
• Develop reusable frameworks for recurring data problems and cross-system testing.
• Prototype proofs of concept based on regulatory rule text and program requirements.
• Translate requirements into testable logic, data models, and prototype solutions.
• Create visualizations, diagrams, and documentation communicating findings.

Skills

Python

SQL

Data analysis

Data engineering

Regulatory knowledge

Education

Bachelor’s degree or equivalent experience

Master’s degree preferred

Tools

Jira

Confluence

GitHub

Pandas

DuckDB

Job description

This role is a senior analytical professional within Markets Transformation & Program Execution. The individual will apply data analysis, data engineering, quantitative methods, and emerging technologies to support transformation programs, inform business decisions, and accelerate the translation of regulatory and business requirements into practical solutions. Working with product owners, risk specialists, business subject matter experts, technology teams, and program leaders, the individual will analyze complex data, evaluate data quality, prototype decision logic, and design sustainable data solutions. The role requires the ability to translate business and regulatory concepts into structured analytical approaches and communicate effectively with both business and technical stakeholders. This role's primary focus is applied analysis, data engineering, quantitative problem-solving, rapid prototyping, and the design of agentic workflows. The successful candidate will independently structure ambiguous problems, apply a disciplined and evidence-based approach, and deliver high-quality analytical outputs that support Markets priorities. The role will work with sensitive, confidential, and controlled business data. The individual must apply appropriate data-handling, access-control, documentation, and governance practices throughout the analytical lifecycle.

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.

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.

Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi. Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

This job opening is for an existing job vacancy.

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