Customer Data Analyst

Ookla® is a global leader in connectivity intelligence, offering unparalleled network insights through the combined expertise of Speedtest®, Downdetector®, RootMetrics®, and Ekahau®. Ookla’s complementary datasets combine crowdsourced and controlled, public and private collection methods, QoS and QoE metrics, and more to unlock correlations and actionable insights — helping organizations optimize networks, enhance digital experiences, and create better connected experiences for end-users.Our team is a group of people brought together through passion and inspired by possibility. We are looking for team members who love solving problems, are motivated by challenges, and enjoy turning clever ideas into exceptional products. When you work for us, you are using Ookla data and insights to advance our mission of better connectivity for all.

 

Role Summary:As a Customer Data Analyst within our Professional Services team, you will play a critical role in transforming raw customer data into actionable insights. You will be responsible for collecting, cleaning, analyzing, and interpreting data related to customer engagements, service delivery, product adoption, and overall customer health. Your analysis will directly inform strategic decisions, optimize our service offerings, enhance customer experience, and contribute to the overall success of our customers and the Professional Services organization. You will collaborate closely with Professional Services leadership, consultants, project managers, and customer success managers to understand their data needs and deliver impactful reports and analyses.Responsibilities:

• Data Collection and Management:
• Identify and gather relevant customer data from various sources, including CRM systems (e.g., Salesforce, Dynamics 365), project management tools (e.g., Jira, Asana), customer success platforms (e.g., Gainsight, ChurnZero), support ticketing systems (e.g., Zendesk, ServiceNow), and other relevant databases.
• Ensure data accuracy, integrity, and consistency through data cleaning, validation, and transformation processes.
• Develop and maintain data pipelines and data models to facilitate efficient data retrieval and analysis.
• Data Analysis and Interpretation:
• Conduct exploratory data analysis to identify trends, patterns, and correlations related to customer behavior, service utilization, project outcomes, and customer satisfaction.
• Develop and apply statistical techniques and data visualization methods to extract meaningful insights from complex datasets.
• Analyze key performance indicators (KPIs) relevant to Professional Services, such as project profitability, service delivery efficiency, customer adoption rates, time-to-value, and customer retention.
• Identify opportunities for process improvement, service optimization, and enhanced customer engagement based on data analysis.
• Reporting and Communication:
• Design and generate regular and ad-hoc reports and dashboards that effectively communicate key findings and insights to stakeholders across the Professional Services organization.
• Present data-driven recommendations and actionable insights to Professional Services leadership and team members in a clear and concise manner.
• Collaborate with stakeholders to define reporting requirements and ensure that reports meet their specific needs.
• Develop and maintain documentation for data sources, methodologies, and reporting processes.
• Collaboration and Support:
• Partner with Professional Services leadership to define data-driven strategies and objectives.
• Support project teams and consultants with data analysis to inform project planning, execution, and risk mitigation.
• Work closely with Customer Project Managers to identify at-risk customers and opportunities for proactive engagement based on data insights.
• Contribute to the development of data literacy within the Professional Services team.

Qualifications:

• Bachelor's degree in a quantitative field such as Data Science, Statistics, Mathematics, Economics, Computer Science, or a related discipline.
• 10+ years of experience in a data analysis role, preferably within a Professional Services, SaaS, or technology-focused organization.
• Proven ability to collect, clean, analyze, and interpret complex datasets from various sources.
• Strong proficiency in data analysis tools and programming languages such as SQL, Python (with libraries like Pandas, NumPy, Matplotlib, Seaborn), and data visualization tools (e.g., Tableau, Power BI, Heavy.ai).
• Experience working with CRM systems (e.g., Salesforce), customer success platforms (e.g., Gainsight, ChurnZero), and other relevant business applications.
• Solid understanding of statistical concepts and methodologies.
• Excellent communication and presentation skills, with the ability to effectively convey technical findings to both technical and non-technical audiences.
• Strong problem-solving and critical-thinking skills with a keen attention to detail.
• Ability to work independently and collaboratively in a fast-paced environment.  
• A strong understanding of Professional Services methodologies and customer lifecycle management is a plus.

Preferred Qualifications:

• Experience with data warehousing concepts and technologies.
• Familiarity with machine learning techniques and their application to business problems.
• Experience building and maintaining data pipelines using ETL tools.
• Certifications in relevant data analysis or business intelligence tools.