Senior Data Analyst

In this role you will:

• Own defining, tracking, and monitoring business KPIs for the Central Platforms Product team.
• Partner with product managers to create hypotheses, define quantitative goals, and design experiments for roadmap projects
• Partner with engineering to improve data collection through data infrastructure design, data pipelining, and warehousing solutions
• Collaborate with cross-functional teams, including business stakeholders, developers, and data engineers, to identify data requirements, gather feedback, design and implement solutions.
• Conduct exploratory data analysis to discover patterns and insights to inform future strategy. 
• Gather, compile, and extract meaningful insights from complex datasets, using statistical techniques and machine learning algorithms when applicable.
• Summarize and evangelize your findings across the company; providing Executives, Product Managers, Engineering teams, and other Data Analysts with deep-dive quantitative analyses in an immediately usable format, extracting key insights from extensive, complex data sets
• Proactively find opportunities to take analytics framework into the next level and lead stakeholders to adopt new frameworks and methodologies
• Take ownership of ambiguous and complex analytical assignments

We could be a Match if you have:

• 5+ years of progressive experience using quantitative analysis to make business-focused recommendations
• 3+ years of analytics experience working directly with product managers or embedded within a product team
• Experience with data warehousing, data pipelining solutions a plus
• Familiarity with machine learning concepts and algorithms
• Proven technical data analytics skills in working with large amounts of data at different levels of aggregation, from raw telemetry to metric stores. 
• Working knowledge of trust and safety analytics metrics (fraud signals, bad actor patterns, etc.)
• Strong understanding of incrementally as well as sizing business problems and opportunities
• Understanding of basic statistical concepts such as confidence interval, normal distribution, correlation, linear regression, and multivariate testing
• Strong communication skills at different levels of organizational hierarchy
• Proactive skill set that encompasses problem identification, analysis, solution definition, results, and communication
• Proficiency with SQL, R and Python (or equivalent)
• In depth experience with data visualization and analytical tools (Amazon QuickSight, Mode Analytics, Power BI, Looker)