We're looking for a highly analytical, curious, and self-driven problem solver who enjoys tackling complex business and data challenges. This role is about discovering better ways to operate, evaluating opportunities, investigating discrepancies, and turning ideas into scalable business solutions.
Working directly with company leadership, you'll identify operational inefficiencies, evaluate strategic initiatives, build business cases, implement revenue data reconciliation, and partner with stakeholders to move ideas from concept to implementation. Projects range from data analysis to AI, automation, process redesign, and new business initiatives.
The ideal candidate is comfortable with ambiguity, learns quickly, communicates well, and takes ownership from problem identification through implementation.
What you'll be doing:
- Learn how commission and revenue data flows in from multiple suppliers, each with their own statement format, and help in redesigning data ingestion processes
- Allocate and validate commissions data, investigate, reconcile and resolve commission discrepancies, prioritizing issues based on financial impact and business urgency.
- Be the go-to contact for advisors and other stake holders with questions about commissions
- Perform and improve commissions allocation and validation processes
- Identify operational and strategic opportunities elsewhere in the business, using the same investigate-and-fix approach
- Analyze data, processes, and stakeholder feedback to identify root causes.
- Build business cases, evaluate ROI, and recommend practical solutions.
- Research AI tools and emerging technologies to improve efficiency and decision-making.
- Lead initiatives from discovery through implementation.
- Partner with development teams to translate business requirements into scalable solutions.
- Build dashboards and analyses when needed to support decisions.
What you'll bring:
- 1–4 years of experience in strategy, analytics, consulting, engineering, operations or finance.
- Quantitative degree preferred.
- Strong analytical thinking and communication skills.
- Advanced Excel skills.
- SQL, Power BI, Python, or similar tools are a plus and can be learned.
- Demonstrated curiosity about AI and enthusiasm for using AI tools to improve business outcomes.
- High ownership, initiative, and accountability.
- Ability to thrive in ambiguity and manage multiple priorities.