**Responsibilities:** + Working with business partners, define business use cases for using statistical and advanced analytics to improve existing and create new efficient and effective O&PS business processes. + Create detailed business requirements for functional (e.g., business processes, rules) and non-functional (e.g., data, security) capabilities. + Work closely with management to prioritize business and information needs. + Develop and implement data collection strategies involving different systems to optimize and maintain data quality: collect, clean, transform, analyze data as needed. + Utilize primary and/or secondary data sources; maintain databases and data systems. + Profile data sources using SQL and other data discovery tools in support of data quality and business intelligence design efforts. + Identify, analyze, and interpret trends and/or patterns in complex data sets; prepare inventories of items which could be developed/trained using analytical tools like machine learning. + Perform other duties and responsibilities as assigned. + Basic data governance concepts and practices within the financial services industry. + Understanding of ETL and data flow principles. + Data models, database design development, data mining and segmentation techniques. + Statistics, including hypothesis testing. + Various machine learning and other data science techniques. + Python programming. + Data visualization using tools like Qlik Sense and/or Tableau. + Financial Services or Wealth Management industries is preferred. **Skill in** + Retrieving, blending, and analyzing data from a variety of sources and structures using tools such as Alteryx. + Using various scripting tools (e.g. Python, R, SQL, etc.). + Building models that business units understand, use, and acknowledge as value-adding. + Combining various sources of data to create meaningful information and dashboards. + Report writing and data visualization tools (Qlik Sense, Tableau, PowerBI, etc.). **Ability to** + Focus on needs of internal and external clients; identify and understand issues, problems and opportunities; compare data from different sources to draw conclusions; proactively suggest next steps to business units; and maintain productive client relationships. + Clearly convey information and ideas through a variety of media to individuals or groups in a manner that engages the audience and helps them understand and retain the message; explain technical concepts to non-technical audiences. + Challenge conventional thinking and work with stakeholders to identify and improve the status quo. + Use effective approaches for choosing courses of action, developing appropriate solutions; and recommending/taking action that is consistent with available facts, constraints and potential risks. + Demonstrate satisfactory levels of technical and professional skills, knowledge in position-related areas; remain current with developments and trends in data science. + Develop and build collaborative relationships to facilitate the accomplishment of work goals. + Deliver work-products on schedule.