POSITION SUMMARY: The Data Scientist II will support Wescom by performing data mining, data cleansing, and aggregation to prepare data, conduct analysis, identify patterns and trends, and interpret insights to effectively build Machine Learning (ML) models to solve business problems. The Data Scientist II will develop a deep understanding of Members, their journeys, behaviors, and experience to effectively describe and prepare data to design, develop, evaluate, deploy, optimize, and maintain the ML models. The successful candidate will play a key role in supporting the Business Analytics Department objectives, including the deployment, maturation, and adoption of advanced analytical capabilities and Machine Learning models to further strategic business objectives. The position will report to the Data Science and Business Analytics Manager and work closely with the VP of Business Analytics and cross-functional stakeholders throughout Wescom. ESSENTIAL POSITION FUNCTIONS: Formulate advanced analytics projects based on relevant business problems and use cases. Describe and prepare data, conduct exploratory data analysis, design and develop Machine Learning (ML) models, test model accuracy and efficacy, and deploy, optimize, and maintain models in Production. Develop automated processes to cleanse, integrate, and analyze complex datasets using advanced analytics, Machine Learning (ML), and other Data Science routines. Effectively utilize internal & external data to extract relevant features and create datasets to build Machine Learning (ML) models to predict behavior and business outcomes in support of strategic priorities. Interpret and communicate model results, key insights, and recommendations to technical and non-technical stakeholders, including executives, through effective presentations utilizing slide decks, data visualizations, and dashboards. Responsible for developing and deepening organizational knowledge across cross-functional data domains, continuously learning, collaborating, and driving advanced analytics projects from start to completion with minimal managerial guidance. Responsible for ensuring Machine Learning (ML) platform and model operation (ML Ops) performance meets established service standards and SLAs. Independently engages, collaborates, and works with internal and vendor subject matter experts to resolve issues and document Root Cause Analysis for management reporting. Develops and documents processes following best practices, corporate policies, and any applicable regulatory requirements for use case ideation, data preparation, model building, deployment, maintenance, and governance. Ensures on-time and high-quality delivery of assignments and demonstrates effective prioritization, planning, and delivery of competing priorities. Supports and cross-trains more junior team members on advanced analytics and Machine Learning (ML) concepts, best practices, and effective use of Wescom’s ML platform capabilities. EDUCATION, EXPERIENCE, SKILLS, AND ABILITIES: Bachelor’s degree in Engineering, Statistics, Computer Science, Data Science, or other similar disciplines is required. Master’s degree or graduate-level coursework in a related discipline is highly preferred. Minimum of 3 years of hands-on experience building, deploying, and maintaining Machine Learning (ML) models; preferrably for a Financial Services organization. An in-depth understanding of Machine Learning and modeling algorithms such as decision trees, random forests, neural networks, SVM, KNN, Time Series Forecasting, Window Method, Gaussian Process, text mining, NLP, etc. is required. Hands-on Data Science and advanced analytics professional experience navigating, querying, and combining diverse data sets across multiple systems and translating complex data findings into actionable insights. Professional experience using SAS, SQL, Python, R, and/or other programming tools & languages to build and deploy Machine Learning (ML) models for advanced analytics projects. Hands-on experience training, testing, evaluating, deploying, optimizing, and maintaining Machine Learning (ML) models using statistical methods such as principal component analysis, model performance metric evaluation, data drift analysis, champion-challenger methods, etc. Team player with great interpersonal and communication skills in collaborating and problem-solving with individuals at all levels of the organization. Able to analyze and understand complex and technical concepts and be able to explain them in layman’s terms to management and non-technical stakeholders. Able to conduct hypothesis testing through the design and build of complex experiments is desired. Detail-oriented self-starter with good self-organization and time management skills. Able to work in a fast-paced work environment with concurrent and shifting priorities. Experience working on cross-functional advanced analytics business use cases. Applied knowledge and experience working in the Customer (or Member) analytics data domain is highly desired. Applied knowledge of Data Management best practices is highly desired. COMPUTER SKILLS: Strong knowledge and applied work experience using SQL to effectively query, filter, aggregate, sort, and massage data across disparate data sources is required. Hands-on work experience using Python for Machine Learning (ML), visual, and text analytics is required. Knowledge and hands-on working experience with Machine Learning (ML) platforms such as DataRobot, Dataiku, Alteryx, H2O.ai, Abacus.ai, etc. is a plus. Proficient in Microsoft PowerBI; knowledge of other dashboarding technologies is a plus. Proficient in Microsoft applications (Word, Excel, PowerPoint, and Outlook). Hands-on working experience with Snowflake or other cloud Data platform(s) is a plus. Hands-on working experience with AWS SageMaker is a plus. Working experience with Credit Union or Bank core systems, data platforms, and business use cases is a plus. Working experience with SAS Base, Enterprise Guide, Enterprise Miner, Visual Analytics, or similar SAS packages is a plus. MATHEMATICAL SKILLS: Ability to build/apply statistical models to draw causal inferences. Ability to add, subtract, multiply and divide using whole numbers, common fractions, and decimals. Ability to compute rates, ratios, and percentages. PHYSICAL DEMANDS: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is frequently required to stand; walk; sit; use hands to finger, handle or feel; reach with hands and arms, climb or balance, stoop kneel, crouch, crawl; talk or hear and taste or smell. The employee must occasionally lift and/or move up to 10 pounds. Vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus. WORK ENVIRONMENT: This position may qualify as Remote or Hybrid with a home base at one of Wescom’s offices. The Remote or Hybrid status may be discontinued by Wescom in its sole discretion at any time and for any reason or no reason, with or without notice by Wescom or Employee. The work environment characteristics described here are representative of those an employee encounters while performing functions of this job. The noise level in the work environment is moderately quiet. It is a non-smoking environment. The above job requirements are representative of minimum levels of knowledge, skills, and abilities. The marginal functions have not been included. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This job description in no way implies that these are the only duties to be performed. An employee will be required to follow any other job-related instructions and duties as requested by the supervisor and/or management.