Data Scientist

Here’s just some of what you’ll do:

• Design and build scalable solutions using AI and Machine Learning (Generative AI, Natural Language Processing, Reinforcement Learning, and Time Series predictions) in document understanding, financial forecasting, and optimizing infrastructure resource utilization.
• Own the model building and refining from identifying business problems, hands-on coding to curate training dataset, analyze data & validate models to delivering production grade solutions at scale.
• Drive high-level and detailed technical design conversations.
• Own and deliver documentation and methods required for model review with the model governance teams.
• Be responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, and CI/CD tool integration
• Work closely with stakeholders across Technology, Finance and business unit portfolio leaders to define scope, requirements and incorporate cost drivers, allocation methods, and infrastructure nuances
• Ensure best practices are aligned with Enterprise Architecture and Decision Science COEs
• Develop SQL queries, scripts and routines to automate data processing and enhance the model’s accuracy and efficiency
• Generate insightful data visualization and reports to aid in decision-making
• Lead training sessions and create comprehensive documentation to empower end users to leverage the cost model effectively
• Provide technical mentorship to team members at junior levels
• Function as an active member of an agile team

Are you up for the challenge?  Here’s what you should have:

• Master’s degree in Data Science, Mathematics, Computer Science, Engineering, Information Systems, or related STEM fields
• 3+ years full lifecycle product development and engineering leadership in highly available, highly scalable, and high throughput systems
• Experience in deploying out-of-the box LLMs and Generative AI solutions including setting up Vector DBs, Graph-RAG and extensive testing of LLMs. Hands-on knowledge of Chain-of-Thought, Tree-of-Thought, Graph-of-Thought prompting strategies. Must demonstrate deep knowledge of testing frameworks for Generative AI
• Demonstrated experience with knowledge graphs
• Experience in building and owning data science solutions and pipelines within the MLOps ecosystem in Vertex AI
• Hands-on expertise with handling distributed (multi-tiered) systems and automated testing – unit and performance testing
• Demonstrated experience in building and deploying a diverse set of Machine Learning (GLM, GBM, Neural Networks), Time series forecasting models and NLP solutions at scale
• Proficiency and Hands-on Experience with Git, CI/CD tools, Elasticsearch, and a solution in each category: Orchestration, Container, Model Serving, Observability, and Feature Store
• Strong proficiency in programming with Python, Machine Learning libraries and APIs (TensorFlow, Keras, PyTorch, ScikitLearn, H20.ai, XGBoost)
• Experience in data visualization and observability with a focus on real time serving and monitoring of time series data with alerts
• Strong project management skills and effective stakeholder management skills, coupled with a continuous improvement mindset
• Excellent presentation and communication skills, capable of explaining complex technical choices in simple terms to a diverse audience
• Experience in Financial Services industry is preferred
• Thorough understanding of enterprise infrastructure technologies (Compute, Storage, Network, Mainframe) to inform model development is preferred.