Partner with counterparts in product, engineering, data infrastructure, finance, and operations departments to produce the analyses, datasets and data models necessary to measure and inform product development.
Develop deep systemic knowledge of data from operational systems and product data to build strategies for continuous improvement of the reporting capabilities of that data.
Write SQL queries and use analytics tools to create datasets that support product, operational, and revenue reporting needs, including statistical modeling and forecasting.
Build scalable and sustainable tools and dashboards to automate reporting and generate insights that will allow the team to quickly and accurately see how our products and processes are performing.
Proactively identify areas outside the regular stream of business requests where analytics can add value - have that “canary in a coal mine” mentality when it comes to data.
Influence an experimentation culture and build the data structures and processes necessary to use experimentation to improve product development.
Act as a trusted advisor to stakeholders bringing insights and analyses forward in product and leadership forums as a cross-functional partner.
Work cross-functionally with Engineering, Data/Analytics Engineering, Business Intelligence, and Data Platform teams to ensure a unified approach to analytics.
Provide training and enablement for self-service capabilities using the analytics tool stack.

Requirements

Bachelor's degree in Business, Computer Science, Information Systems, or a related field with a minimum of 8 years of experience in Product Analytics, Data Analysis, Data Science or related field; or a Master’s degree with 6 years of related experience; or a PhD with 3 years of experience; or equivalent experience.
Strong understanding of how analytics supports product development and experience with metric design and standard reporting practices.
Robust methods for QAing data to ensure accuracy and completeness.
Strong SQL & statistical data modeling skills (e.g. SQL, Python, R).
Advanced knowledge of ETL, data pipelining practices, and data model design.
Experience translating stakeholder needs and requirements into data architecture and dashboard and reporting assets.
Hands-on experience with product analytics and dashboarding tools (i.e. Amplitude, Heap, Pendo, Tableau, Hex).
Experience with A/B testing, experimentation and behavioral analytics.
Excellent communication and storytelling skills, capable of distilling complex data into clear, actionable insights for stakeholders at all levels.
A self-starter mindset, excited to build something from scratch and evolve it over time.

Benefits

Competitive compensation and benefits programs
Cash compensation (overtime, bonus/commissions, if eligible)
Flexible work arrangements
Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

SQLstatistical modelingdata analysisdata scienceETLdata pipeliningdata model designA/B testingPythonR

Soft skills

communicationstorytellingself-starter mindsetcross-functional collaborationinfluencingtraininganalytical thinkingproblem-solvingstakeholder managementcontinuous improvement