We are looking for a business-oriented and analytically strong Manager, who understands the business, thinks analytically, communicates confidently with senior leaders, and can guide a team that needs strong direction on methodology, structure and quality. The right candidate is analytically strong, commercially grounded, and moving toward the consultative end of the spectrum, someone who owns critical processes, shapes decisions, and elevates the thinking around them.
The role requires strong business acumen, stakeholder management, project management, analytical judgment, and leadership capability. This person must be able to raise the quality of thinking within the team and help move the function towards insights, decision support, and business value creation.
This role reports to the Senior Manager, Global Sales Operations.
What You Will Own
Commercial Intelligence and Decision Support
- Translate business priorities into structured workstreams by defining the right approach, methodology, data inputs, assumptions, outputs, and decision points.
- Move the team beyond reporting by ensuring outputs provide clear insights, business implications, and recommended actions.
- Challenge assumptions, close logic gaps, validate methodology, and raise the standard of thinking before work reaches stakeholders.
- Proactively identify where data, process, and insights can improve sales strategy, pipeline governance, segmentation, forecasting, target-setting, SIP, or commercial performance.
- Partner with Sales Leadership, Finance, Product Management, IT, BI, Data Analytics, and regional teams as a credible, business-facing commercial intelligence partner.
Sales Process Ownership and Project Management
- Lead and govern critical Sales Operations processes, including SIP, target-setting, forecasting support, advance analytics and provide end-to-end process leadership across inputs, quota modeling, cross-functional coordination, system implementation with IT, communication, in-year tracking, issue resolution, and measurement.
- Build and manage structured project plans across complex, multi-stakeholder processes with hard deadlines, dependencies, risks, and accountability requirements and provide leadership summaries.
- Bring structure to ambiguous problems, drive cross-functional alignment, and move work forward without needing step-by-step direction.
- Improve process discipline, documentation, governance, and repeatability across assigned workstreams.
- Communicate insights, risks, trade-offs, and recommendations confidently to senior directors and VPs, including in high-scrutiny situations.
- Represent Commercial Analytics and BI in senior forums, including leadership reviews, pipeline governance meetings, sales performance discussions, and cross-functional planning sessions.
- Influence decisions through structured thinking, data-backed recommendations, and strong business judgment.
Team Leadership, Data and Digital Enablement
- Lead, coach and provide the team supporting analytics on clear direction on methodology, structure, output quality, stakeholder communication, and business relevance.
- Ensure dashboards, reports, and recurring outputs are accurate, business-relevant, decision-oriented, documented, and repeatable.
- Promote practical use of AI and automation to improve speed, documentation, productivity, insight generation, and repeatability.
- Build a team culture focused on ownership, accountability, curiosity, continuous improvement, and business impact.
Required Qualifications
- Master's degree in Business, Finance, Economics, Engineering, Analytics, Data Science, or a related field.
- 10+ years of experience in Sales Operations, Commercial Analytics, Commercial Finance, Strategy, Business Operations, Revenue Operations, or a related function with significant analytical and business-facing responsibility.
- Strong business acumen with the ability to understand commercial metrics, pipeline, topline, bottom-line, forecasting, target-setting, SIP, and what they mean to a sales organization.
- Consultative problem-solving mindset with the ability to frame ambiguous business questions, structure the work, identify decision points, and guide stakeholders toward practical recommendations.
- Proven ability to communicate findings, risks, trade-offs, and recommendations clearly and confidently to senior leadership.
- Strong project management skills with the ability to run multi-stakeholder, cross-functional processes with hard deadlines, dependencies, and accountability requirements.
- Demonstrated ability to guide analysts on methodology, structure, quality, and business relevance — not just review finished outputs.
- Strong analytical judgment, including the ability to define the right approach, challenge assumptions, validate logic, and convert findings into practical recommendations.
- Advanced Excel capability and hands-on experience transforming large, complex, real-world datasets into analysis-ready formats, including data scrubbing, validation, structuring, and purposeful summarization.
- Comfort working with imperfect data, practical tool constraints, and evolving business requirements. A candidate who has only worked with clean, pre-processed data will not succeed in this role.
- Proficiency in at least one BI tool, such as Power BI or Tableau.
- Ability to operate independently in ambiguous, fast-moving, or unstructured environments.
Preferred Qualifications
- MBA or postgraduate qualification in Business, Finance, Analytics, Engineering, or a related field.
- Experience with SIP analytics, quota-setting, target validation, revenue planning, forecasting, or pipeline governance.
- Familiarity with Salesforce or another CRM platform as a commercial data source.
- Exposure to advanced analytics, predictive modeling, AI, automation, or data science applications in a commercial or sales operations context.
- Prior experience in B2B, manufacturing, industrial, technology, or complex sales environments.
- Experience preparing leadership review materials, business cases, executive summaries, or decision documents.
- Experience partnering with BI, Data Analytics, IT, or data engineering teams to improve data quality, reporting automation, and scalable decision-support tools.
