We are seeking a highly skilled and experienced Assistant Vice President (AVP), Data Science & AIML Engineer, to join our growing team. The ideal candidate will possess a strong blend of data science expertise, machine learning engineering capabilities, and proven hands-on experience in developing and deploying AI/ML solutions in a production environment. This role requires deep proficiency in Python, a solid understanding of CI/CD pipelines, and experience building high-performance APIs, particularly with FastAPI. You will be instrumental in designing, building, and deploying advanced analytical models and machine learning systems that address complex business challenges. **Key Responsibilities:** + **Model Development:** Design, develop, and implement advanced machine learning models (e.g., predictive, prescriptive, generative AI) to solve complex business problems, from initial data exploration and feature engineering to model training and evaluation. + **MLOps & Deployment:** Lead the deployment of AI/ML models into production environments, ensuring scalability, reliability, and performance. + **API Development:** Build and maintain robust, high-performance APIs (using frameworks like FastAPI) to serve machine learning models and integrate them with existing applications and systems. + **CI/CD Implementation:** Establish and manage continuous integration and continuous deployment (CI/CD) pipelines for ML code and model deployments, promoting automation and efficiency. + **Data Engineering:** Collaborate with data engineers to ensure optimal data pipelines and data quality for model development and deployment. + **Experimentation & Optimization:** Conduct rigorous experimentation, A/B testing, and model performance monitoring to continuously improve and optimize AI/ML solutions. + **Code Quality & Best Practices:** Promote and enforce best practices in software development, including clean code, unit testing, documentation, and version control. + **Technical Leadership:** Mentor junior team members, contribute to technical discussions, and drive the adoption of new technologies and methodologies within the team. + **Stakeholder Communication:** Effectively communicate complex technical concepts and model results to both technical and non-technical stakeholders. **Required Skills & Qualifications:** + **Education:** Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field. + **Experience:** + Minimum of 6+ years of professional experience in Data Science, Machine Learning Engineering, or a similar role, with a strong track record of deploying ML models to production. + Proven experience in a lead or senior technical role. + **Technical Proficiency:** + **Python:** Expert-level proficiency in Python programming, including experience with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn) and deep learning frameworks (e.g., TensorFlow, PyTorch). + **FastAPI:** Strong hands-on experience designing, developing, and deploying RESTful APIs using FastAPI. + **CI/CD:** Solid understanding and practical experience with CI/CD tools and methodologies (e.g., Jenkins, GitLab CI, GitHub Actions, Azure DevOps) for MLOps. + **MLOps:** Experience with MLOps platforms, model monitoring, and model versioning. + **Cloud Platforms:** Experience with at least one major cloud provider (e.g., AWS, Azure, GCP) for deploying and managing ML workloads. + **Database Skills:** Proficiency in SQL and experience working with relational and/or NoSQL databases + **Machine Learning:** Deep understanding of machine learning algorithms, statistical modeling, and data mining techniques. + **Problem Solving:** Excellent analytical and problem-solving skills, with the ability to translate complex business problems into actionable data science solutions. + **Communication:** Strong verbal and written communication skills, with the ability to articulate technical concepts to diverse audiences. **Preferred Skills & Qualifications** + Experience with containerization technologies (e.g., Docker, Kubernetes). + Familiarity with big data technologies (e.g., Spark, Hadoop). + Experience in the financial services industry. + Knowledge of generative AI techniques and large language models (LLMs). + Contributions to open-source projects or relevant publications. This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. ------------------------------------------------------ **Job Family Group:** Technology ------------------------------------------------------ **Job Family:** Applications Development ------------------------------------------------------ **Time Type:** Full time ------------------------------------------------------ **Most Relevant Skills** Please see the requirements listed above. ------------------------------------------------------ **Other Relevant Skills** For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ _Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law._ _If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review_ _Accessibility at Citi (https://www.citigroup.com/citi/accessibility/application-accessibility.htm)_ _._ _View Citi’s_ _EEO Policy Statement (https://www.citigroup.com/global/eeo-aa-policy)_ _and the_ _Know Your Rights (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf)_ _poster._ Citi is an equal opportunity and affirmative action employer. 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