Manager of Product Analytics & Data Science

Your Role & Mission

As the (Senior) Manager of Product Analytics & Data Science, you will be responsible for driving the vision, tactics, and execution of key qualitative insights that shape Apollo’s overall strategy and product roadmap. This role will be mission critical in standardizing how we scale and implement statistical analysis (e.g. hypothesis testing, regression analysis, causal inference), A/B testing, and other key measurement techniques across the firm that act as the qualitative lynchpin to our decision-making. In addition to implementing this aforementioned foundational infrastructure and executing on key analyses yourself, you will be managing a team of product analysts / data scientists that are functionally aligned to particular product squads, empowering them to make data driven decisions that increase activation, engagement, and retention across all of our surface areas. 

As Apollo continues to scale, data-driven decision making and predictive insights will be a critical asset to the company and thus, this role will have high visibility, agency, and autonomy to expand qualitative analysis at enterprise scale.  You and your team of product analysts will work closely with various product teams, data platform, business intelligence and product engineering teams, fostering collaboration, innovation, and continuous improvement. This role requires a strong blend of technical expertise, strategic thinking, and leadership skills to guide our products' evolution and deliver maximum value to our customers. You will be reporting to the Head of Business Intelligence & Analytics within the broader Revenue Operations organization.

Responsibilities

• Own the curation and execution of the Product Analytics & Data Science roadmap, partnering with our product leadership team to directly tie and correlate business strategy (OKRs and initiatives) into adjacent key predictive models, rich analyses, experiments, and department-specific reports/dashboards that aid in the measurement and execution of the key “Outcomes” listed above
• Provide tactical support for various data needs such as experiment setup, impact sizing, deep dive data exploration, and the development of critical self-service funnel or behavioral dashboards for product managers and squad engineering leaders to consume to help the real-time efficacy of key programs and features being launched to customers
• Partner alongside data platform and business intelligence to map out the end-to-end flow of our product funnels with relevant events to be instrumented, metrics to be calculated, etc., manifesting in highly-governed tracking events, certified golden tables, and cross-functional data work streams that becomes the key infrastructure under the hood of statistical and predictive models
• Partner alongside our machine learning team directly to help build various models in the context of personalization (i.e. auto-suggestions in search filters, highly targeted and contextually relevant feedback and recommendations gleaned from conversation/transcripts), forecasting (i.e. scoring and predictive insights on particular account and contact profiles best suited for engagement), and other key AI/ML-driven levers (i.e. improved sentiment analysis in sequences) that help improve our core product offering
• Act as a hybrid individual contributor and team lead, helping tangibly execute on the roadmap of critical team deliverables while unblocking, mentoring, and enable your direct reports in order to build a best-in-class quantitative decision arm for the entirety of our product organization

Qualifications

• Degree in Analytics, Applied Mathematics, Economics, Statistics or related analytical field of study or equivalent combination of training and experience
• Deep and rich experience in working with critical exploratory analysis projects related to cohorting, time series analysis, funnel analysis/optimization is required
• Expert-level proficiency with regard to influencing product strategy with SQL, A/B testing, machine learning, statistical analysis and/or related capabilities like R, Python, SAS, etc. is required
• Direct experience managing, mentoring, and upleveling individual contributors that are product analysts and/or data scientists
• Current or former role(s) supporting SaaS (Product Led Growth) companies with qualitatively unraveling gaps and influencing recalibrated activation metrics (i.e. aha/habit moments) is a huge plus