Senior Data Analyst

Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. As a highly motivated Senior Data Analyst, you will be responsible for independently owning and driving analytics initiatives within the Operations team. Your role will involve translating data into actionable insights that enhance efficiency, decision-making, and key business Key Performance Indicators (KPIs). You will collaborate with stakeholders from Operations, Product, Data Engineering, and Business Strategy to identify opportunities for process optimization, automate decision-making, and establish scalable analytics frameworks. This high-impact role demands deep analytical skills and the ability to influence business strategy through data-driven insights. Your responsibilities will include driving analytics strategy by identifying areas for efficiency improvements and cost optimization within Operations, utilizing advanced analytics techniques such as inferential modeling, causal analysis, and experimental design to generate actionable insights, designing and implementing A/B tests to optimize key processes, developing frameworks to measure operational KPIs and business impact, translating complex data insights into clear recommendations using data storytelling and visualization tools, collaborating cross-functionally to align analytics initiatives with business needs, enhancing scalability and automation efforts to improve efficiency, and promoting data analysis best practices while mentoring junior analysts. To be successful in this role, you should possess 5+ years of experience in data analytics with a focus on Operations, Business Strategy, or Process Optimization. Expertise in SQL, Python, and working with relational cloud databases and unstructured datasets is essential. You should have experience designing A/B tests, strong statistical knowledge, experience in operations analytics, proficiency in data visualization tools, the ability to work independently and influence business decisions through data-driven recommendations, strong problem-solving skills, and a proactive mindset to identify business opportunities using data. Bonus points if you have experience with ML/AI applications in operational efficiency, familiarity with event-tracking frameworks and behavioral analytics, strong data storytelling skills, and prior experience in a fast-paced, high-growth environment with a focus on scaling data analytics.,