Senior Data Analyst (Operations Analytics)

As a Senior Data Analyst at Zinnia, you will play a crucial role in driving analytics initiatives within the Operations team by translating data into actionable insights that enhance efficiency, decision-making, and key business KPIs. Your responsibilities will include: - Drive analytics strategy: Independently own and drive key analytics initiatives in Operations, identifying areas for efficiency improvements and cost optimization. - Advanced analytics & measurement: Utilize inferential modeling, causal analysis, and experimental design to generate actionable insights beyond basic dashboards. - Experimentation & testing: Design and implement A/B tests to measure the impact of operational improvements on processes such as fraud detection, customer interactions, and compliance. - Operational KPIs & business impact: Develop frameworks to measure Turnaround Time (TAT), Cost Per Transaction, SLA adherence, and other key operational metrics to facilitate data-driven decision-making. - Data storytelling & visualization: Translate complex data insights into clear recommendations using visual storytelling techniques in tools like Power BI. - Cross-functional collaboration: Collaborate with stakeholders across Operations, Data Engineering, and Product to align analytics initiatives with business needs. - Scalability & automation: Partner with Data Engineering to enhance data pipelines, data models, and automation efforts for improved efficiency. - Thought leadership & best practices: Drive data analysis best practices, mentor junior analysts, and foster a culture of analytical rigor and excellence. Qualifications required for this role include: - 5+ years of experience in data analytics, with a focus on Operations, Business Strategy, or Process Optimization. - Proficiency in SQL, Python, and working with relational cloud databases (Redshift, BigQuery, Snowflake) and unstructured datasets. - Experience in designing A/B tests, statistical knowledge, and operations analytics. - Hands-on experience with data visualization tools (Power BI, Tableau, Looker) and effective presentation skills. - Strong problem-solving skills, proactive mindset, and ability to influence business decisions through data-driven recommendations. If you have experience with ML/AI applications, event-tracking frameworks, or prior experience in a high-growth environment, it would be considered a bonus. As a Senior Data Analyst at Zinnia, you will play a crucial role in driving analytics initiatives within the Operations team by translating data into actionable insights that enhance efficiency, decision-making, and key business KPIs. Your responsibilities will include: - Drive analytics strategy: Independently own and drive key analytics initiatives in Operations, identifying areas for efficiency improvements and cost optimization. - Advanced analytics & measurement: Utilize inferential modeling, causal analysis, and experimental design to generate actionable insights beyond basic dashboards. - Experimentation & testing: Design and implement A/B tests to measure the impact of operational improvements on processes such as fraud detection, customer interactions, and compliance. - Operational KPIs & business impact: Develop frameworks to measure Turnaround Time (TAT), Cost Per Transaction, SLA adherence, and other key operational metrics to facilitate data-driven decision-making. - Data storytelling & visualization: Translate complex data insights into clear recommendations using visual storytelling techniques in tools like Power BI. - Cross-functional collaboration: Collaborate with stakeholders across Operations, Data Engineering, and Product to align analytics initiatives with business needs. - Scalability & automation: Partner with Data Engineering to enhance data pipelines, data models, and automation efforts for improved efficiency. - Thought leadership & best practices: Drive data analysis best practices, mentor junior analysts, and foster a culture of analytical rigor and excellence. Qualifications required for this role include: - 5+ years of experience in data analytics, with a focus on Operations, Business Strategy, or Process Optimization. - Proficiency in SQL, Python, and working with relational cloud databases (Redshift, BigQuery, Snowflake) and unstructured datasets. - Experience in designing A/B tests, statistical knowledge, and operations analytics. - Hands-on experience with data visualization tools (Power BI, Tableau, Looker) and effective presentation skills. - Strong problem-solving skills, proactive mindset, and ability to influence business decisions through data-driven recommendations. If you have experience with ML/AI applications, event-tracking frameworks, or prior experience in a high-growth environment, it would be considered a bonus.