Analyst-Data Science

How will you make impact in this role: Execute product roadmap initiatives for the Investments Management ecosystem across LUMI, TM1, and related BI platforms, partnering with Product Managers and Technology teams to deliver business value. Partner with business stakeholders to gather, analyze, and document business requirements, translating them into user stories, functional specifications, and acceptance criteria. Assist in managing and refining the product backlog by tracking requirements, documenting enhancements, and supporting prioritization activities. Perform detailed data analysis to identify business trends, process improvement opportunities, and actionable insights that support product decisions. Support the development, maintenance, and enhancement of foundational data products on LUMI (e.g., Acquisitions Database, Offer Data Layer, EIDM, PO3), ensuring data accuracy, consistency, and usability. Collaborate with Technology teams during design, development, testing, and deployment to ensure solutions meet business requirements and quality standards. Execute functional testing, validate business outcomes, and support User Acceptance Testing (UAT) activities for new product capabilities and enhancements. Build and maintain dashboards, reports, and self-service analytics solutions using Tableau, Power BI, or similar visualization tools to enable informed decision-making. Monitor product performance through defined metrics such as adoption, data quality, and operational efficiency, and recommend continuous improvements. Support data governance initiatives by validating data quality, documenting business rules, and ensuring adherence to enterprise standards. Research, evaluate, and pilot opportunities to leverage Gen AI capabilities to improve productivity, automate manual processes, and enhance user experiences. Partner with Product, Finance, and Technology teams to analyze business problems, identify solution options, and support delivery of scalable data and technology solutions. Prepare product documentation, process flows, release notes, training materials, and stakeholder communications to support successful product adoption. Support recurring planning and governance activities, including monthly AENB 81 and VCC documentation, reporting, and operational processes. Strong analytical mindset with the ability to interpret data and provide actionable business insights. Excellent attention to detail and commitment to delivering high-quality work. Ability to manage multiple priorities and deliver results in a fast-paced environment. Strong organizational and documentation skills. Curiosity and willingness to learn new technologies, product management practices, and AI capabilities. Effective collaboration and relationship-building skills across cross-functional teams. Ability to work through ambiguity, ask thoughtful questions, and propose practical solutions. Proactive mindset with a continuous improvement approach to processes and products. Basic understanding of AI/ML concepts, data analytics, or automation technologies is a plus. Passion for building scalable, user-centric data products that deliver measurable business value. Experience in business analysis or data analytics with exposure to large and complex datasets. Foundational understanding of product management concepts, Agile methodologies, and software development lifecycle. Experience translating business requirements into user stories, process documentation, or functional specifications. Proficiency in SQL/Bigquery/Lumi and Hive / Yellowbrick; Python knowledge is preferred. Experience with Tableau, Power BI, TM1, or similar reporting and visualization platforms is preferred. Understanding of data modeling, data governance, and data quality principles. Strong analytical and problem-solving skills with the ability to synthesize complex information into meaningful insights. Excellent written and verbal communication skills with the ability to collaborate across business and technology teams. Bachelor's degree in Finance, Mathematics, Statistics, Computer Science, Information Systems, Engineering, or a related field. Familiarity with Gen AI tools and productivity platforms (e.g., ChatGPT, Gemini, Claude, Microsoft Copilot) is preferred.