Director, Machine Learning & Data Science

Design and build personalization engines/learning systems using advanced machine learning and statistical techniques Help the company in identifying tools and components, and building the infrastructure for AI/ML Research and brainstorm with internal partners to identify advanced analytics opportunities to advance automation, help with knowledge discovery, support decision-making, gain insights from data, streamline business processes, and enable new capabilities Perform hands-on data exploration and modeling work on massive data sets. Perform feature engineering, train the algorithms, back-test models, compare model performances and communicate the results Work with senior leaders from all functions to explore opportunities for using advance analytics Provide technical leadership mentoring to talented data scientists and analytics professionals Guide data scientists and engineers in the use of advanced statistical, machine learning, and artificial intelligence methodologies Provide thought leadership by researching best practices, extending and building new machine learning and statistical methodologies, conducting experiments, and collaborating with cross functional teams Develop end-to-end efficient model solutions that drive measurable outcomes. These technical skills include, but not limited to, regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory, stochastic systems, Bayesian inference, statistical techniques, deep learning, supervised learning, unsupervised learning Solid understanding and hands on experience working with big data, and the related ecosystem, both relational and unstructured. Executing on complex projects, extracting, cleansing, and manipulating large, diverse structured and unstructured data sets on relational – SQL, NOSQL databases Working in an agile environment with iterative development & business feedback Providing insights to support strategic decisions, including offering and delivering insights and recommendations Experience in statistics & analytical modeling, time-series data analysis, forecasting modeling, machine learning algorithms, and deep learning approaches and frameworks. Deliver robust, scale and quality data analytical applications in a cloud environment.