Summary

The Analytics Team at Chainalysis is looking for a Staff Business Data Analyst to help define and create the next generation of company performance metrics and visibility tools. You’ll join the Business Technology, Data and Analytics Team in our centralized analytics unit and work with stakeholders across Finance, Sales, Customer Success, Marketing, People & Product to define metrics and scale our analytics capabilities.

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. The analytical tools and dashboards you build will help us understand the drivers of success metrics and make informed business decisions. 

In this role, you’ll:

1. Access and analyze all of Chainalysis’ datasets including sales, customer, finance, product usage, and other datasets.
2. Treat our internal data as a product and help to scale the company’s analytics platforms, work with the Data Strategy & Operations team to train folks to leverage BI tools, and provide your colleagues with actionable insights.
3. Work with the Data Engineering team to build tools and mechanisms to consolidate and update data regularly, making data easily accessible to all stakeholders in the company.
4. Translate business questions into quantitative questions, uncover the inputs into our success metrics and develop actionable insights that influence our leadership teams to identify critical areas of improvement.
5. Develop a deep understanding of our business, synthesize findings and provide strategic recommendations.
6. Maintain KPI metrics and planned data analysis roadmaps for our stakeholder teams.

We’re looking for candidates who have: 

1. 6+ Professional work experience in a hands-on analytics function with Revenue Operations and/or Finance Operations and mentoring junior staff.
2. Educational background in Computer Science, Engineering, Math, Statistics, Economics, Analytics, or a quantitative discipline preferred.
3. Experience querying data sets across company Marketing Automation, CRM, ERP, Financial Modelling and Product Analytics applications (we use Marketo, Netsuite, Salesforce, Adaptive and Pendo).
4. Experience in inventing new metrics and visualizations such as, LTV:CAC, Avg Customer Life, ARR, ACV, Customer Health Score, conducting root cause analysis and developing reporting/visualization solutions (e.g., Tableau, Quicksight)
5. Proven ability to translate ambiguous business and product questions into quantitative problem statements through structure, complex analysis, implement large scale analytical solutions and drive business insights
6. Experience in enterprise SaaS environments with a strong understanding of Go-To-Market strategies and Quote-To-Cash processes
7. Advanced skills in SQL, Tableau, Data Warehouse solutions (e.g., Redshift, Databricks, Snowflake) and exposure to statistical concepts such as regression, time series, correlation, segmenting and forecasting.
8. Excellent organizational skills including prioritization of multiple concurrent projects while still delivering timely and accurate results.
9. Excellent oral, presentation and written communication skills - you’re passionate about storytelling via data!.
10. A Just Do It attitude and ability to move with urgency and customer obsession.
11. An ownership mindset - acts and makes decisions on behalf of the company, not just the team. Never heard of the words “not my job”.

Nice to have experience:

1. Knowledge and experience with data pipeline technologies, data modeling (star schemas, snowflake, aggregation tables), basic data architectures (compute and reporting clusters).
2. Parsing structured and unstructured data in JSON, parquet and other formats
3. Experience working with NetSuite
4. Python
5. dbt

Technologies we use:

1. Marketo
2. Salesforce
3. NetSuite
4. Adaptive Insights
5. Pendo
6. Redshift 
7. Databricks
8. Tableau

Skills

• Analytical Thinking
• Communications Skills
• Database Management
• Operations
• Python
• SQL
• Team Collaboration