At Citi, our mission is simple: We responsibly provide financial services that enable growth and economic progress.
Formerly known as Global Consumer Banking, Citi’s Personal Banking & Wealth Management business reflects our streamlined, strategic focus on U.S. Personal Banking – inclusive of our product lines of Branded Cards, Retail Services (white label credit cards) and U.S. Retail Banking (our branches) – and Global Wealth Management (self-service digital wealth management and advisors). This new name clearly distinguishes Citi amongst our competitors. Our model is distinct: personalized financial guidance supported by leading digital capabilities and complemented by well-placed physical locations in leading urban markets within the U.S., EMEA, Asia, and LatAm. And as consumer expectations continue to evolve rapidly, our unique model is well-positioned to evolve with them – providing our customers with seamless service and delivering advanced digital experiences for today and tomorrow.
As a Lead Data Scientist on our U.S. Personal Banking Analytics team, you’ll provide data science and technical support for answering data-driven questions that drive decision making. You’ll analyze our vast internal customer data, external data sources, and other relevant internal data sources to identify areas of opportunity and effectively communicate your findings to others on your team and to leadership. You’ll partner with stakeholders to understand their evolving requirements, collaborate with other analysts on the team, and share findings that are innovative, insightful, and drive decision making.
You have a passion for data, digital solutions, and for making sure data is fit for purpose. You’ll have a strong understanding of, and real-world experience in statistics (even better if you also know machine learning!) You're a collaborator with an affinity for problem-solving, reimagining the future, and abstract reasoning. You are curious, resilient, empathetic, collaborative, confident and are always eager to learn new things.
On any given day, you will be challenged by three types of work – Innovation, Business Intelligence and Data Science and you will be responsible for:
Translating business needs to analytical problems that can be answered with data science
Understanding multiple data science techniques and knowing which technique is best for a given situation
Owning a unique stream of work within the larger data science portfolio for a particular sub-business
Designing and developing new frameworks and automation tools to enable teams to consume and understand data faster and with absolute transparency
Using your expert coding skills across several languages like SQL and Python to support other analysts and Data Scientists
Applying the fit for purpose machine learning techniques to complex business problems, frequently in collaboration with other Data Scientists
Collaborating with multiple teams in high visibility roles and owning solutions end-to-end
Partnering with Data Analysts, who may help you better understand business needs and can complete some of the tasks at hand
Producing ideas for exploratory analysis that shape future projects and growth initiatives
Providing models that for others will use to create dashboards and reports to regularly communicate business results to executive leadership
Explaining your findings to business stakeholders in simple language that helps them make decisions quickly
Ensuring adherence to best practices supporting Citi's Program, Project, and Data Management Standards by appropriately assessing 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, as well as effectively supervise the activity of others and create accountability with those who fail to maintain these standards.
Our ideal candidate will have:
6+ years of experience (less with the right academic experience)
A Masters or Ph.D. in statistics, data science, computer science, engineering, or another technical discipline
Experience financial services preferred
Experience coding in Python, R, or Pyspark. Understanding of SAS a plus
Ability in strategic thinking and the ability to frame business problems
Top notch communications skills and the ability to translate complex concepts into simple terms so senior executives can make decisions quickly
Experience working in Agile teams and using Scrums to organize work a plus
An influencer who communicates clearly and frequently to both technical analysts and non-technical business leaders
Intellectually curious, consistently seeking and developing new opportunities
Job Family Group:
Specialized Analytics (Data Science/Computational Statistics)
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