data Analytics team lead

PassportCard Labs is where innovation meets impact. As the technological powerhouse behind PassportCard, we design and build cutting-edge solutions that revolutionize the insurance industry. Whether it’s real-time claims payments or predictive analytics, our Labs team is at the forefront of driving change and shaping the future of insurance. Ready to innovate with us? We are seeking a highly skilled and motivated Data Analytics Team Lead to join our dynamic and growing Data Group. In this role, you will lead our analytics team, be responsible for analyzing complex datasets, and design, develop, and maintain analytics infrastructure and BI products. You will play a pivotal role in transforming data into actionable insights, driving business growth, and enhancing our data-driven decision-making process. You should have a strong background in data analysis, statistical modeling, and machine learning. Working within our unique Insurtech hub, you will provide actionable insights to drive business decisions and play a key role in the company's growth and expansion. You will collaborate closely with business stakeholders, data scientists, data engineers, and tech leads to implement cutting-edge solutions that enhance our competitive stance. Our ideal candidate has experience with various data streams, a passion for data and analytics processes, and a broad business perspective. Equally important, you are a friendly, collaborative, and communicative team member. Roles and Responsibilities:
* Team Leadership & Management:?Lead, mentor, and develop a team of Data Analysts to ensure high-quality analytical deliverables. Foster a collaborative and results-oriented team environment, conduct core methodologies, and provide technical guidance, training, and career path evolution for team members.
* Data Analysis & Insights:?Design, develop, and maintain analytical products using Power BI, Data Bricks, and Tableau. Perform deep-dive analyses to derive actionable insights that support business objectives. Utilize Python and SQL for data extraction, transformation, manipulation, and analysis, and implement best practices for analytics and reporting.
* Cross-Company Collaboration:?Partner with business units to understand their analytics needs and provide effective solutions. Communicate insights effectively to technical and non-technical stakeholders and support strategic decision-making with data-driven recommendations.
* Partnership with Tech Stakeholders:?Collaborate with data engineers, data scientists, R&D, Product, and AI teams to define data product scope, objectives, and deliverables. Promote cross-functional collaboration to align analytics projects with broader AI and data science initiatives.
* Data Projects Leadership:?Manage multiple data projects from inception to completion, ensuring timely delivery and high-quality outcomes. Continuously improve the performance, accuracy, and efficiency of analytics solutions.