Staff Product Data Analyst

The Analytics Team at Chainalysis is looking for a Staff Product Data Analyst to help define and create the next generation of deep dive and performance metrics visibility tools. Our ideal candidate is comfortable in a nascent and fast-paced space with a lot of ambiguity, enjoys translating complex business questions into well-defined quantitative problems, and is capable of building scalable analytics solutions to answer these questions. You’ll join the Business Technology, Data and Analytics Team in our centralized analytics unit and work with stakeholders across Product, Marketing, Engineering, Product Design, Sales & Customer Success to define metrics and scale our analytics capabilities. The analytical tools and dashboards you build will help us understand the drivers of success metrics and make informed business decisions.

In one year you’ll know you were successful if...

• You are an expert in accessing and analyzing all of Chainalysis’ datasets including product usage, sales, customer, financial system, and other datasets.
• You know our product portfolio, how our users engage with them and have driven insights to key stakeholders
• You own and can speak to key metrics across the product portfolio with a deep expertise in Chainalysis specific data and analytics concepts.
• You’ve treated our internal data as a product and helped to scale the company’s analytics platforms, trained folks to leverage BI tools, and provided your colleagues with actionable insights
• You’ve built tools and mechanisms to consolidate and update data regularly to make data easily accessible to all stakeholders in the company
• You’ve translated business questions into quantitative questions, uncovered the inputs into our success metrics and developed actionable insights that have influenced our leadership teams to identify critical areas of improvement
• You’ve up-kept company KPI metrics and planned data analysis roadmaps to meet the operational and performance tracking requirements across teams
• You’ve presented complex yet actionable findings or insights to leadership that have directly impacted the business.

A background like this helps:

• Educational background in Computer Science, Engineering, Math, Statistics, Economics, Analytics or a quantitative discipline preferred
• Professional work experience in a hands-on analytics or data science function with proven quantitative orientation, manipulating large datasets for time series analysis, cohorting, segmentation and forecasting.
• Experience in inventing new metrics, conducting root cause analysis, A/B testing and developing reporting/visualization solutions (e.g., Tableau, Quicksight)
• Proven ability to translate ambiguous business and product questions into quantitative problem statements, structure complex analysis, implement large scale analytical solutions and drive business and product insights.
• Advanced skills in SQL, Tableau, Product Analytics tools (e.g., Pendo), Data Warehouse solutions (e.g., Redshift)
• Knowledge and experience with data pipeline technologies, data modelling (star schemas, snowflake, aggregation tables), basic data architectures (compute and reporting pclusters).
• Fluency with statistical analytics and a programming language such as R, Python etc.
• Excellent organizational skills including prioritization of multiple concurrent projects while still delivering timely and accurate results.
• Excellent oral, presentation and written communication skills - you’re passionate about storytelling via data!
• A Just Do It attitude and ability to move with urgency and customer obsession.
• An ownership mindset - acts and makes decisions on behalf of the company, not just the team. Never heard of the words “not my job”.

The following would differentiate you:

• Engineering experience or familiarity with technologies such as AWS, Pendo, Airflow, Hadoop or Spark
• Previous experience as a Data Scientist or leveraging python for data analysis
• Deep understanding of SaaS KPIs
• Experiencing mentoring and/or leading junior analysts