Data Scientist

The Specialized Analytics Intermediate Analyst role at Citi is a developing professional position that involves dealing with problems independently and having the flexibility to solve complex issues. This role requires integrating specialized knowledge with industry standards and practices, understanding how the team collaborates with others to achieve objectives, and applying analytical thinking along with data analysis tools. Attention to detail is crucial for making judgments and recommendations based on factual information, and dealing with variable issues with potential business impact. The TTS Analytics team at Citi provides analytical insights to various functions within the global Treasury & Trade Services business, such as Product, Pricing, Client Experience, and Sales. The team focuses on enhancing client experience, driving acquisitions, cross-sell, and revenue growth by extracting relevant insights, identifying business opportunities, and using big data tools and AI/ML techniques to achieve data-driven business outcomes in collaboration with business and product partners. As a Specialized Analytics Intermediate Analyst (C11) in the TTS Analytics team, the role involves working on multiple analyses throughout the year to address business problems related to client experience. This includes leveraging various analytical approaches, tools, and techniques, working with multiple data sources, and providing data-driven insights to business partners and stakeholders. The role requires endless curiosity, working with large and complex data sets, evaluating, recommending, and supporting the implementation of business strategies. Key responsibilities include ideation on analytical projects, working with structured and unstructured data, documenting data requirements, data processing, cleaning, exploratory data analysis, statistical models/algorithms, data visualization techniques, and assessing risks when making business decisions. Building partnerships with cross-functional leaders is also essential. Qualifications for this role include 5-8 years of relevant experience in data science, substantial experience in resolving business problems in the financial services industry, utilizing text data for business value using NLP and LLM, developing analytical tools, applying ML, DL, and Gen AI techniques, working with complex data sources, and proficiency in Python and SQL. Skills required include strong analytical skills, logical reasoning, problem-solving ability, formulating analytical methodology, identifying trends and patterns, and manipulating data from big data environments. A Master's degree in Engineering, Technology, Statistics, Economics, or similar quantitative disciplines is preferred. Proficiency in Python, SQL, PySpark, MS Excel, and PowerPoint is essential, with experience in Tableau considered a plus. This job description provides an overview of the work performed, and additional job-related duties may be assigned as required.,