• Serve as the senior analytics lead and primary advisor to senior and executive stakeholders within a major financial institution client. • Translate complex business needs into advanced analytics solutions that drive measurable improvements in acquisition, engagement, and retention. • Define and evolve the client’s analytics roadmap, introducing enhanced modeling approaches, refined data strategies, and real-time decisioning capabilities that support compliant, high-impact marketing execution. • Oversee the full analytics lifecycle, including data preparation, model development, validation, deployment, scoring, activation, attribution, and reporting. • Monitor predictive and recommendation model performance, reviewing outputs, dashboards, and KPIs to confirm targets are met, identify gaps, and recommend data-driven improvements. • Ensure adherence to financial-industry requirements, including fair lending, model governance, audit, and data-privacy standards. • Deliver clear, executive-level insights and recommendations grounded in model performance and customer behavior. • Advance the analytics function by introducing improved methodologies, tools, and processes. • Identify and recommend new predictive and prescriptive modeling approaches that strengthen precision and return on investment. • Lead documentation, testing, and monitoring practices that align with enterprise governance and risk expectations. • Partner with cross-functional teams to implement real-time marketing solutions and continuously refine model performance. • Manage and mentor analytics managers and data scientists working on the financial institution portfolio. • Ensure projects are executed on time, within scope, and at a consistently high standard of quality. • Foster a culture of accountability, innovation, and compliance discipline.

• Partner directly on growth initiatives to build, ship, measure incrementality of bookings/attach rate/revenue, and optimize 0-to-1 customer-facing features • Thought partnership with Product to define strategy, sequence iteration, scale impact via science frameworks and as the go-to tech lead around data, experimentation, and domain understanding • Build observational causal inference models to deeply understand guest intent, identify underlying mechanisms, and build data products to measure impact, and inform feature objectives and tradeoffs • Champion AI-enabled Product Understanding, to scale data-driven frameworks, robust measurement, and compelling storytelling of data learnings to guide recommendations and roadmaps with senior leaders

• Analyze large-scale manufacturing data, including **sensor, batch, recipe, and production line data** • Develop analytics solutions to identify **defects, scrap, rework, and process deviations** • Perform **root cause analysis** and **multivariate process analysis** to uncover drivers of quality issues • Build **anomaly and defect detection models** to proactively identify process failures • Partner with manufacturing, quality, and operations teams to translate findings into actionable improvements • Deliver measurable outcomes such as **cost reduction, waste minimization, and quality improvement**

• Analyze large volumes of structured and unstructured data. • Design, develop, and implement statistical models and machine learning algorithms to predict outcomes and solve complex business problems. • Collect, clean, and preprocess data from multiple sources. • Develop dashboards and data visualizations to effectively communicate findings and insights. • Collaborate closely with IT, marketing, and other business teams to understand requirements and deliver data-driven solutions. • Stay up to date with industry trends, tools, and technologies in data science to continuously improve processes and products.