Citi Group Data Science Gen AI Dev Manager - Hybrid 

United States, Florida, Tampa 

45323757

You will be joining us right at the beginning of our journey. As a senior member of the team, you will be actively coding, designing, and deploying the solution. As such, we need an innovative, opinionated, and creative leader who have previous real-world experience.

Responsibilities

• Lead end-to-end data science projects, from problem formulation to model deployment.
• Collaborate closely with cross-functional teams, including technology and business stakeholders to define project requirements and deliverables.
• Apply advanced statistical and machine learning techniques to analyze large, complex datasets and extract actionable insights.
• Integrate generative LLM techniques. This could include chat, Retrieval Augmented Generation, and automated scenario simulation and optimization.
• Develop predictive models, algorithms, and data-driven solutions to optimize business process, improve process transparency, and drive strategic decision-making.
• Design and conduct experiments, tests, and casual inference analysis to evaluate the effectiveness of interventions and initiatives.
• Mentor and coach team members, providing guidance on best practices, methodologies, and tools in data science and machine learning.
• Stay-up-to-date with the latest developments in data science, machine learning, and related fields, and evaluate emerging technologies for potential adoption.
• Strong architecture skills – as this is a new application, we are looking for a leader who can conceptualize what needs to be built and then participate in the actual build.

What we’ll need from you:

• 7+ years of professional experience in data science, with good foundation in statistical analysis and machine learning
• Hands on experience with LLM (commercial and open source), LangChain, LlamaIndex, Retrieval Augmented Generation, and Vector Databases
• Proficiency in programing languages such as Python and familiarity with libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, Scipy, Pandas, etc.
• Solid understanding of experimental design, hypothesis testing, and casual inference methods
• Experience in pattern recognition and predictive modeling.
• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Strong problem-solving and critical-thinking abilities, with a demonstrated ability to tackle open-ended problems and drive projects to completion.
• Knowledge of software engineering best practices, including version control, agile SDLC, testing and deployment pipelines
• Financial industry experience would be a plus.

Anticipated Posting Close Date:

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