Data Analyst

Responsibilities

We are representing a global SaaS organization seeking a highly analytical Data Analyst to support and scale their partner ecosystem. In this role, you will analyze data across partner sales performance, customer usage, licensing, and marketing to provide insights that drive revenue growth, customer adoption, and long-term retention. Your work will directly inform leadership decisions on investment priorities and channel business growth.

Your key responsibilities will include:

• Partner Performance Analysis: Analyze partner contributions 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: Analyze customer movement between direct sales and partner channels, identifying opportunities for expansion and retention.
• 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 enable sales, marketing, and partner teams to 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.

What We're Looking For

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) is a must. Experience with CRM systems (e.g., Dynamics CRM, PRMs), customer success platforms, commission tools, marketing platforms, and sales intelligence tools is 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.

How We Work With You

Candidates interested in this position should apply directly through Get A Job.ai. Our talent team will conduct an initial screening to assess your qualifications and fit for the role. If selected, we will submit your profile to our client for consideration. Please note that we ask candidates not to contact the client directly—all communication regarding this opportunity should go through Get A Job.ai to ensure a smooth and professional process.

Pay

Compensation details will be discussed during the screening process based on your experience and qualifications.

Get A Job.ai is an equal opportunity recruiter. We welcome applications from all qualified candidates regardless of race, color, religion, sex, national origin, age, disability, or any other protected characteristic. We are committed to fostering an inclusive hiring process.