Sales Operations Analytics Specialist
The Sales Operations Analytics Specialist is responsible for delivering advanced analytics, actionable insights, and scalable reporting solutions to improve sales performance and operational efficiency.
This role combines sales analytics, Power BI dashboard development, and AI-driven insights to enable data-led decision-making across the revenue organization. The role partners closely with Sales, Revenue Operations, Finance, and Commercial teams to enhance forecasting, pipeline visibility, and commercial performance.
Job Description
Key Responsibilities
1. Sales Performance & Commercial Analytics
- Analyse sales performance across pipeline, bookings, revenue, and conversion metrics
- Identify trends, risks, and opportunities within the sales funnel
- Deliver insights on:
- Pipeline health and coverage
- Win/loss drivers
- Sales productivity and performance
- Support leadership with data-driven recommendations
2. Forecasting & Predictive Analytics
- Support and enhance forecasting processes using data and predictive models
- Analyse pipeline progression and forecast risk
- Develop predictive insights using statistical methods and AI techniques
- Partner with Sales Ops and Finance to improve forecasting accuracy
3. Power BI Dashboard Development
- Design, build, and maintain interactive dashboards and reports using Power BI
- Develop scalable data models and visualisations for:
- Sales performance
- Pipeline and forecasting
- Deal and pricing analytics
- Ensure dashboards are intuitive, actionable, and aligned to business needs
- Automate reporting and reduce manual data processes
4. AI & Advanced Analytics
- Apply AI and machine learning techniques to improve:
- Forecasting accuracy
- Lead and opportunity scoring
- Deal outcome prediction
- Explore and implement AI-driven insights to support sales decision-making
- Work with data teams (where applicable) to integrate advanced analytics solutions
- Identify opportunities to leverage generative AI for:
- Sales insights summarisation
- Automated reporting
- Data-driven recommendations
5. Data Management & Governance
- Ensure high-quality, reliable data within CRM and reporting systems
- Define and maintain data standards and metric definitions
- Identify and resolve data quality issues
- Collaborate with Sales Ops to improve data capture and processes
6. Deal & Pricing Insights
- Analyse deal-level data including:
- Pricing and discount trends
- Deal cycle times
- Margin and profitability
- Support Deal Desk and Pricing teams with data-driven insights
- Provide recommendations to improve commercial outcomes
7. Strategic Analysis & Projects
- Support strategic initiatives such as:
- Territory planning
- Quota setting
- Sales coverage models
- Conduct deep-dive analysis to answer key business questions
- Provide insights to support go-to-market strategy
Key Skills & Experience
Required
- 3–6 years experience in Sales Operations, Analytics, or similar role
- Advanced Power BI skills (data modelling, DAX, dashboard design)
- Strong analytical and problem-solving capabilities
- Experience working with CRM systems (e.g.HubSpot, Dealhub)
- Strong Excel / data manipulation skills
- Ability to translate data into business insights
Preferred
- Experience with AI / machine learning techniques (e.g., Python, R, or similar)
- Familiarity with SQL and data querying
- Experience in SaaS, enterprise sales, or services environments
- Understanding of sales metrics and revenue operations frameworks
- Experience integrating data from multiple sources (CRM, ERP, etc.)
Key Competencies
- Analytical Thinking – ability to interpret complex datasets and trends
- Technical Expertise – strong Power BI and data modelling capability
- Commercial Acumen – understands revenue drivers and deal dynamics
- Innovation Mindset – applies AI and automation to improve outcomes
- Communication – clearly presents insights to stakeholders
- Attention to Detail – ensures accuracy and data integrity
KPIs / Success Measures
- Adoption and usage of Power BI dashboards
- Forecast accuracy improvement
- Data quality metrics (completeness, accuracy)
- Impact of analytics on sales performance and decision-making
- Reduction in manual reporting effort through automation
- Delivery of AI-driven insights and predictive models