Data Scientist-Mid Level

We are seeking a hardworking and dedicated Data Scientist-Mid Level to work remotely and convene with team members at least 4 times per year. Uses sophisticated techniques that integrate traditional and non-traditional datasets and method to enable analytical solutions. Applies predictive analytics, machine learning, simulation, and optimization techniques to generate management insights and enable customer-facing applications; participates in building analytical solutions maximizing internal and external applications to deliver value and build competitive advantage. Translates sophisticated analytical and technical concepts to non-technical employees. Job Requirements Tasks: • Identifies and leads existing and emerging risks that stem from business activities and the job role. • Ensures risks associated with business activities are successfully identified, measured, supervised, and controlled. • Follows written risk and compliance policies, standards, and procedures for business activities. • Partners with analysts across the organization to fully define business problems and research questions; Supports SMEs on cross matrixed teams to take on highly sophisticated work critical to the organization. • Integrates and extracts relevant information from large amounts of both structured and unstructured data (internal and external) to enable analytical solutions. • Conducts sophisticated analytics using predictive modeling, machine learning, simulation, optimization and other techniques to deliver insights or develop analytical solutions to achieve business objectives. • Supports Subject Matter Experts (SME's) on efforts to develop scalable, efficient, automated solutions for large scale data analyses, model development, model validation and model implementation. • Works with IT to research architecture for new products, services, and features. • Develops algorithms and supporting code such that research efforts are based on the highest quality data. • Translates sophisticated analytical and technical concepts to non-technical employees to enable understanding and drive advised business decisions. Minimum Requirements: • Master's degree in Computer Science, Applied Mathematics, Quantitative Economics, Statistics, or related field; OR 6 years of related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree. • 4 years of related experience in predictive modeling, large data analysis and computer science. • Proficient knowledge of the function/discipline and proven application of knowledge, skills, and abilities towards work products. • Proficient level of business insight in the areas of the business operations, industry practices and emerging trends. • Experience in data mining and statistical analysis. • Knowledge of Data Science principals and experience with data science methodologies. • Experience with any one of the following statistical and predictive modeling approaches: Gaussian Process; Markov Models; Hierarchical Clustering; K-Means; Linear Regression; Logistic Regression; Monte Carlo Simulation; Neural Networks. Preferred Experience: • Relevant banking domain knowledge particularly in areas such as AML, Fraud, Consumer Disputes, or Central Operations. • Strong Python, SQL skills. • Project experience with Graph Databases such as Neo4j, AWS Neptune or similar. • Worked with data platforms such as Hive in Hadoop, Spark, Snowflake. • Exposure to natural language processing (NLP), deep learning, computer vision. • Model risk experience, or hands-on experience taking models through development and model risk validation, at a financial institution guided by OCC 2011-12 and FRB SR 11-7. • Proven ability to effectively communicate (written and oral) complex analytical and technical concepts to both technical and non-technical employees. Apply Job!