
1001 - 5000 employees
Founded 1927
💼 Consulting
🏥 Healthcare
📣 Marketing
💰 $650M Post-IPO Debt on 2017-06
Consulting • Healthcare • Marketing
Ziff Davis is a multi-billion dollar digital media and internet company, home to over 40 leading brands in technology, shopping, gaming and entertainment, connectivity, health and wellness, cybersecurity, and martech. With a focus on mergers and acquisitions, Ziff Davis has deployed around $3 billion in capital, leveraging its deep industry knowledge, technological expertise, and investment acumen. The company is committed to corporate responsibility, emphasizing diversity, equity, and inclusion, as well as environmental, social, and governance practices. Ziff Davis serves millions of customers worldwide, offering a diverse range of digital media and internet services.
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1001 - 5000 employees
Founded 1927
💼 Consulting
🏥 Healthcare
📣 Marketing
💰 $650M Post-IPO Debt on 2017-06
Consulting • Healthcare • Marketing
Ziff Davis is a multi-billion dollar digital media and internet company, home to over 40 leading brands in technology, shopping, gaming and entertainment, connectivity, health and wellness, cybersecurity, and martech. With a focus on mergers and acquisitions, Ziff Davis has deployed around $3 billion in capital, leveraging its deep industry knowledge, technological expertise, and investment acumen. The company is committed to corporate responsibility, emphasizing diversity, equity, and inclusion, as well as environmental, social, and governance practices. Ziff Davis serves millions of customers worldwide, offering a diverse range of digital media and internet services.
• Collect and gather customer data from CRM systems, project management tools, customer success platforms, support ticketing systems, and databases • Ensure data accuracy, integrity, and consistency through cleaning, validation, and transformation • Develop and maintain data pipelines and data models • Conduct exploratory data analysis to identify trends, patterns, and correlations related to customer behavior, service utilization, project outcomes, and customer satisfaction • Apply statistical techniques and data visualization methods to extract insights from complex datasets • Analyze Professional Services KPIs, including 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 • Design and generate regular and ad-hoc reports and dashboards • Present data-driven recommendations and actionable insights to Professional Services leadership and team members • Collaborate with stakeholders to define reporting requirements • Maintain documentation for data sources, methodologies, and reporting processes • Partner with Professional Services leadership to define data-driven strategies and objectives • Support project teams and consultants with data analysis for project planning, execution, and risk mitigation • Work with Customer Project Managers to identify at-risk customers and opportunities for proactive engagement • Contribute to data literacy within the Professional Services team
• Bachelor's degree in a quantitative field such as Data Science, Statistics, Mathematics, Economics, Computer Science, or a related discipline • 3+ years of experience in a data analysis role, preferably within Professional Services, SaaS, or a technology-focused organization • Ability to collect, clean, analyze, and interpret complex datasets from various sources • Strong proficiency in SQL and Python, including Pandas, NumPy, Matplotlib, and Seaborn • Proficiency with data visualization tools such as Tableau, Power BI, or Heavy.ai • Experience with CRM systems such as Salesforce • Experience with customer success platforms such as Gainsight or ChurnZero • Solid understanding of statistical concepts and methodologies • Excellent communication and presentation skills • Strong problem-solving and critical-thinking skills with attention to detail • Ability to work independently and collaboratively in a fast-paced environment • Background check required • Experience with data warehousing concepts and technologies preferred • Familiarity with machine learning techniques preferred • Experience building and maintaining data pipelines using ETL tools preferred • Certifications in relevant data analysis or business intelligence tools preferred
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