Staff Data Scientist – Product Analytics 419 views

What You’ll Bring

• Bachelor’s degree in a quantitative field – Business, Statistics, Psychology or other social science; Master’s preferred, or equivalent experience.
• 5+ years of work experience in advanced analytics related to product logging, clickstream analytics, and A/B testing.
• Strong business acumen, excellent communication skills (written, verbal, and presentation), and the ability to communicate complex ideas in clear, succinct terms to both analytical and non-analytical audiences are a necessity
• Apply descriptive analysis and statistical inference methodologies to support A/B testing with the product & engineering team. Skilled at probing for, evaluating, and synthesizing data from disparate data sources to draw interpretive insights
• Maintain a culture of high-quality output and effectively communicate at all levels, ensure that work gets done well and on time, and respond effectively to unexpected obstacles
• Highly proficient in SQL & Tableau. Working knowledge in Python or Amplitude is a plus.
• Experience in digital products or e-commerce, the insurance industry is a plus.

How You Will Lead

• Their Sr. Data Scientist – Business Analytics will have the opportunity to own product data science and analytics. You will own the development and management of the QB Insurance business KPI reports and lead analytics efforts to measure business outcomes, customer benefit, and customer experiences and produce valuable insights based on the data.
• You will ensure product logging is optimized to provide crystal-clear visibility into the impact and value of new initiatives and product releases. Drive dashboard creation and answer ad-hoc analytic questions and train users to self-serve standard-reports leveraging Amplitude & Tableau.
• You will use considerable expertise and independent judgment in collaborating with peers, data engineers, and stakeholders to methodically and iteratively structure, extract, cleanse, sample, test, validate, and communicate data-driven insights from complex sources and significant volumes of data for complex and unique business problems
• You will lead the full cycle of iterative big data exploration, including hypothesis formulation, sample size calculation, data cleansing, testing, insight generation/visualization, and action planning
• You will communicate the analytical results to leaders, ensuring the data is easily understood by both technical and non-technical audiences.
• It’s essential for you to identify ways to improve the status quo and clearly articulate findings in order to support product strategy with recommendations and in implementation.