Data Scientist Description - This role is responsible for analyzing and interpreting complex data sets using statistical techniques to identify trends, patterns, and insights that can be used to form business decisions and improve organizational performance. The role brings cutting edge perspective on programming techniques for data exploration, mining, preparation, cleansing, manipulation, modeling and validation. The role explores potential opportunities for improving business outcomes with data analytics and improves productivity by recommending efficient, automated processes for large scale data analyses and model development. Responsibilities Leads data mining using modern tools and programming languages. Develops monitoring metrics to reflect real-world model performance and makes recommendations to shape the future direction of models and digital solutions. Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models. Strategizes models to uncover patterns and predictions creating business value and innovation. Manages relationships with business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives. Ties insights into effective visualizations communicating business value and innovation potential. Works with development teams and business units to ensure models are scalable and can be implemented as part of the delivered solution. Leads project team(s) of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance. Represents the data science team for all phases of larger and more-complex development projects. Provides guidance, training and mentoring to less experienced staff members. Qualifications Passion for data science & delivering data driven outcomes. Expert knowledge of Python, SQL, and PySpark. Experience in one or more machine learning frameworks, such as Tensorflow/Keras, PyTorch, Spark MLlib, or Scikit-Learn. Ability to handle large amounts of structured and unstructured data and apply modern data transformation methodologies. Extensive experience using various machine learning algorithms (e.g., classification, regression, clustering) to develop and deploy predictive models Leads data science projects, assuring insights are communicated regularly and effectively, reviewing designs, models and data compliance. Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models. Ability to uncover patterns and predictions from data to create business value and innovation. Strong analytical, problem-solving, and critical-thinking abilities. Ability to deal with ambiguity and work collaboratively in a high paced environment. Excellent interpersonal and project management skills; ability to work across in-person and virtual team environments. Experience visualizing data and conveying insights in a clear and effective manner