• Lead the design, development, and deployment of machine learning models. • Work with large, complex datasets to extract valuable insights and build predictive analytics pipelines. • Collaborate with data engineers to architect and optimize cloud-based data solutions. • Translate business challenges into data-driven solutions using statistical modeling and machine learning techniques. • Automate data workflows and model deployment processes using cloud services and CI/CD tools. • Mentor junior data scientists and contribute to best practices in model development and operationalization. • Communicate findings and strategic recommendations to stakeholders and executive leadership.

• Technical leadership and end-to-end ownership of pricing and revenue ML initiatives • Develop and optimize forecasting and pricing models • Combine time series, demand signals, and heterogeneous data sources • Build a robust measurement system and define clear rollout criteria • Establish standards for backtesting, reproducibility, and versioning • Ensure operational reliability through monitoring, drift detection, and retraining mechanisms • Automate high-impact processes to improve throughput and quality • Design data models in the data warehouse to serve as the basis for reliable metrics • Standardize dashboards for business KPIs • Prioritize requirements together with Product and Revenue teams

• Model Evolution: You develop and optimize our forecasting and pricing models as well as data-driven decision logics, always methodically pragmatic and fully impact-focused. • Signal Hunting: You work with time series, demand signals and heterogeneous data sources. You define features and labels so cleanly that leakage has no chance. • Measurement & Guardrails: You are responsible for evaluation through backtests, robust metrics and segmentations. You support holdouts and A/B setups and ensure the checks between offline and online performance. • Data Visibility: You build dashboards and reports that make model and business KPIs transparent. Your focus is always on the highest data quality. • Smart Workflows: You drive reproducible workflows (versioning, clean pipelines, meaningful tests) and automate recurring analyses and evaluation runs.

• Develop and manage scalable, automated machine learning pipelines, CI/CD workflows, and orchestration frameworks • Design and implement robust model serving infrastructure using platforms like TorchServe, TensorFlow, Triton etc. • Develop scalable inference architectures optimized, with ultra-low latency and high throughput • Ensure seamless model deployment by implementing A/B testing, canary releases, and rollback capabilities • Develop logging, alerting, and monitoring solutions to track model development, and reliability • Improve GPU usage, enable autoscaling, and streamline resource allocation to boost efficiency • Design, implement, and maintain feature stores, robust data pipelines, and scalable storage solutions to efficiently handle large volumes of data