Job description

Join a dynamic team dedicated to enhancing car buying experiences through advanced analytics and innovative strategies. As part of our Data & Analytics organization, you’ll collaborate across functions and channels to deliver impactful solutions and drive career growth. As an Data Scientist lead within the Consumer Community Banking ( CCB) Auto Finance Decision Science team, you will build advanced analytics and machine learning solutions that transform products and customer experiences. You will collaborate across teams to deliver impactful insights and drive strategic growth using cutting-edge technologies. Your deep technical expertise and problem-solving skills will drive significant business impact, as you work on diverse challenges across multiple technologies and applications. You will enable advanced AI technologies, and directly contribute to building the next-generation AI/ML solutions for Chase Auto Finance. You will enable product team data and analytic goals, design and evaluate experiments, build AI-powered analytic solutions, onboard AI/ML platforms, and develop key data assets to drive strategic and operational priorities. You will collaborate with product , business users and technology partners to identify and execute machine learning opportunities, while partnering a global team of data scientists and engineers. Job Responsibilities : • Partner with engineers, research scientists, data engineers, application developers, and product managers to deliver AI-powered products and solutions that transform product workflows and customer interactions. • Design, develop, test, deploy, and support AI platform and capabilities, including foundation model training, LLM inference, similarity search, experimentation, governance, and observability. • Leverage a broad stack of open source and AI technologies such as AWS, VectorDBs, PyTorch, and more. • Invent and introduce state-of-the-art LLM optimization techniques to improve performance, scalability, latency, and throughput, and integrate these models with products. • Contribute to the D&A vision and long-term roadmap of foundational AI systems at Chase Auto Finance. • Handle large, complex datasets from multiple sources; analyze results for quality and statistical relevance; develop insights, methods, and tools using predictive modeling, match pair analysis, time series analysis, simulations, etc. • Partner with product, technology, and business teams to ensure accurate tracking and automation of data capture, transformation, presentment, and security. Align with data owners, contribute to data model and architecture development, and explore data improvement opportunities. • Interact with auto business partners including Business management, Sales, Dealer networks, Finance, Risk, and Controls to drive product management strategies, portfolio growth, and profitability. • Provide actionable insights, communicate key messages clearly, and ensure constant alignment on priorities. Own stakeholder relationships and help shape their agenda. • Support the Managing & Executive Director in overseeing cross functional team execution, roadmap delivery, and commitment to business partner priorities and goals. Required Qualifications, capabilities, and skills : • Bachelor’s degree in computer science, AI, Electrical Engineering, Computer Engineering, or related field plus at least 8 years of experience in D&A platforms and technologies, or Master’s degree in a related field plus at least 6 years of experience. • At least 8 years of experience programming with Python, Go, Scala, or Java. • 6+ years of advanced analytics experience, including creating vision, operating models, product roadmaps, and managing automation backlogs. • Data Engineering: Strong knowledge of data pipelines, ETL, Spark, and distributed computing. • Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search, VectorDBs, guardrails, memory) using Python, C++, C#, Java, Shell. • Proficiency in data analysis and visualization tools such as Tableau, Alteryx, ThoughtSpot, Sigma. • Experience with Teradata, Snowflake, and Databricks. • Demonstrated ability to interpret and communicate concepts clearly to both business and technical audiences, comfortable presenting recommendations to senior management. • Self-starter with strong problem-solving skills, able to manage projects from ideation through completion and deliver actionable insights. • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers. Preferred Qualifications, Capabilities, and Skills: • Proficient in statistical techniques - i.e., data mining, data transformations, text mining, data visualization & advanced analytical methods. (e.g., regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization, NLP) • MLOps: Experience with CI/CD, model monitoring, and ML lifecycle management tools. • Experience with LLM and Gen AI, Proficiency with AWS, Azure for scalable AI/ML workloads. • Passion for staying current with AI research and systems and applying novel techniques in production. • Ability to handle multiple projects, manage conflicting deadlines, and adapt to ambiguity. • Ability to gather data and analytical results and develop clear, compelling presentations and recommendations. • Experience working with business leaders to assess processes and identify automation opportunities to increase efficiency and reduce operational risk.

Requirements