At a Glance
- Tasks: Analyse data to drive partner revenue growth and customer retention.
- Company: Join AvePoint, a leader in tech with a focus on innovation.
- Benefits: Enjoy competitive salary, unlimited PTO, and comprehensive health benefits.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Make a real impact by providing insights that shape business decisions.
- Qualifications: Bachelor's degree in a relevant field and 3+ years of data analysis experience.
The predicted salary is between 50000 - 60000 £ per year.
AvePoint is seeking a highly analytical Data Analyst to support and scale our global partner business. In this role, you will analyze data across our partner ecosystem—including sales performance, customer usage, licensing, and marketing to provide insights into how our partners drive revenue growth, customer adoption, and long-term retention. Your work will help leadership make decisions on where to invest, which partners to prioritise, and how to grow our channel business effectively.
Key Responsibilities:
- Partner Performance Analysis: Analyse how partners contribute to revenue growth, pipeline creation, and customer expansion across regions, channels, and segments.
- Partner Health & Engagement Insights: Develop lifecycle metrics and scorecards to assess partner effectiveness based on engagement, product adoption, customer satisfaction, and training participation.
- Revenue & Forecasting Support: Support reporting on recurring revenue (ARR), renewals, and pipeline, helping leadership understand growth trends and risks within the partner ecosystem.
- Customer & Partner Relationship Insights: Analyse how customers move between direct sales and partners, and identify opportunities for expansion and retention through partner channels.
- Partner Marketing Analytics: Measure the impact of partner-driven campaigns and initiatives on new partner acquisition and existing partner growth.
- Predictive & Strategic Analysis: Build models to identify high-growth partners, at-risk partners, and opportunities to improve partner coverage or investment.
- Dashboarding & Executive Reporting: Create clear, executive-ready dashboards and insights that help sales, marketing, and partner teams take action.
- Cross-Functional Collaboration: Partner with Sales/Go-To-Market, Partner Programs, Marketing, RevOps, and Finance to align on metrics, reporting, and business priorities.
Qualifications:
- Education: Bachelor's degree in Data Science, Statistics, Business Analytics, Computer Science, or a related field. Master's degree preferred.
- Experience: 3+ years of experience in data analysis, preferably in a SaaS or technology environment, with a focus on customer data analytics. Experience in SaaS B2B performance metrics such as Annual Recurring Revenue, Net Recurring Revenue, and Gross Recurring Revenue analysis is a plus.
- Technical Skills: Proficiency in SQL, Python/R, and data visualization tools (e.g., Power BI, Tableau) a must. Experience with customer systems such as CRM systems (e.g., Dynamics CRM, PRMs), Gainsight CS, Everstage Commission, Segment Marketing, DealHub, OutReach, and Zoominfo experience are also a plus.
- Analytical Skills: Strong analytical and problem-solving skills with the ability to interpret complex data and translate it into actionable insights.
- Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively.
- Attention to Detail: High level of accuracy and attention to detail in data handling and analysis.
- Business Acumen: Understanding of sales, marketing, and customer success processes and how data can inform strategy and decision-making.
- Team Player: Ability to work collaboratively in a fast-paced, dynamic environment.
At AvePoint, we strive to offer competitive, fair, and equitable total rewards. The listed salary range represents a good faith estimate, with final offers based on location, experience, skills, and qualifications. The listed range reflects base salary only; our total rewards include base salary, comprehensive benefits (medical, dental, vision, 401(k) with match, unlimited PTO), and depending on the role, bonuses, commissions, or equity (RSUs).
Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.
Data Analyst employer: Socket.dev
Multiverse is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Edinburgh. With a commitment to employee growth through comprehensive upskilling opportunities and a robust benefits package, including generous holiday allowances and health support, Multiverse empowers its team to thrive in the rapidly evolving AI landscape. Join us to be part of a mission-driven company that values diversity and inclusion while shaping the future of education and workforce development.
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We think this is how you could land Data Analyst
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We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Socket.dev
✨Brush Up on Your Statistics
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
