Lead Data Scientist (5 to 8 years)

The Spec Analytics Intmd Analyst is a developing professional role. Deals with most problems independently and has some latitude to solve complex problems. Integrates in-depth specialty area knowledge with a solid understanding of industry standards and practices. Good understanding of how the team and area integrate with others in accomplishing the objectives of the sub function/ job family. Applies analytical thinking and knowledge of data analysis tools and methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results. Breaks down information in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of service provided will affect the effectiveness of own team and other closely related teams.

TTS Analytics C11

What do we do?

• The TTS Analytics team provides analytical insights to the Product, Pricing, Client Experience and Sales functions within the global Treasury & Trade Services business. The team works on business problems focused on enhancing client experience, driving acquisitions, cross-sell and revenue growth.
• The team extracts relevant insights, identifies business opportunities, converts business problems into analytical frameworks, uses big data tools and AI/ML techniques to drive data driven business outcomes in collaboration with business and product partners.

ROLE DESCRIPTION

• The role will be Spec Analytics Intmd Analyst (C11) in the TTS Analytics team
• The role will report to the AVP or VP leading the team.

The role will involve working on

• Multiple analyses through the year on business problems across the client experience for the TTS business
• This will involve leveraging multiple analytical approaches, tools and techniques, working on multiple data sources (unstructured data like emails, call transcripts, etc., client profile & engagement data, transactions & revenue data, digital data, etc.) to provide data driven insights to business partners and functional stakeholders
• As a key contributor to ideation on analytical projects to tackle strategic business priorities
• The role will require endless curiosity, as ambiguity and open-ended questions are a core part of the team’s work
• Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies.
• Identifies and compiles data sets using a variety of tools (e.g. SQL, PySpark, Snowflake) to help predict, improve, and measure the success of key business outcomes.
• Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which may include utilizing statistical models / algorithms and data visualization techniques
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
• Ability to build partnerships with cross-function leaders.

QUALIFICATIONS

Experience:

• 5-8 years of relevant experience in data science.

​Must have substantial experience in:

• Identifying and resolving business problems (around client experience and operations) preferably in the financial services industry
• Utilizing text data to derive business value by leveraging different NLP (mid to expert level prior experience is a must) and LLM.
• Leveraging and developing analytical tools and methods to identify patterns, trends and outliers in data
• Applying ML, DL and Gen AI techniques for a wide range of business problems
• Working with data from different sources, with different complexities, both structured and unstructured
• Have worked on Python and SQL extensively

​Good to have:

• Prior working experience in Customer experience domain (Analysis involving deep dive into CSAT, NPS, Survey feedbacks etc.)
• Have worked on developing Agentic AI solution

Education:

Masters (preferred) in Engineering, Technology, Statistics, Economics or similar quantitative disciplines

Skills:

Analytical Skills:

• Strong logical reasoning and problem-solving ability
• Proficient in converting business problems into analytical tasks, and analytical findings into business insights
• Proficient in formulating analytical methodology, identifying trends and patterns with data
• Has the ability to work hands-on to retrieve and manipulate data from big data environments

Tools and Platforms:

• Expert knowledge in Python, SQL, PySpark and related tools
• Proficient in MS Excel, PowerPoint

Good to have:

• Experience with Tableau

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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