Data Scientist-Mid Level
Posted 2025-03-17We 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.
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