Summary

The Analytics Team at Chainalysis is looking for a 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.

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 leverage 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 execute on data analysis roadmaps for our stakeholder teams.

We’re looking for candidates who have: 

1. Experience querying data sets generated by enterprise Marketing Automation, CRM, ERP and Financial Modeling applications (we use Marketo, Netsuite, Salesforce and Adaptive).
2. 3+ Professional work experience in a hands-on analytics function with Revenue Operations and/or Finance Operations with an emphasis on producing insights to drive business decisions.
3. Experience in building and visualizing metrics 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)
4. Ability to translate ambiguous business questions into quantitative problem statements through structure, complex analysis, implement large scale analytical solutions and drive business insights
5. Experience in enterprise SaaS environments with an understanding of Go-To-Market processes and Quote-To-Cash concepts.
6. Intermediate skills in SQL, Tableau, Data Warehouse solutions (e.g., Redshift, Databricks, Snowflake) and an interest in statistical concepts such as regression, time series, correlation, segmenting and forecasting.
7. A Just Do It attitude and ability to move with urgency and customer obsession.
8. 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. Educational background in Computer Science, Engineering, Math, Statistics, Economics, Analytics or a quantitative discipline preferred.
2. Awareness of data pipeline technologies, data modeling (star schemas, snowflake, aggregation tables), basic data architectures (compute and reporting clusters).
3. Parsing structured and unstructured data in JSON, parquet and other formats
4. Working with any of the following: Marketo, Salesforce, NetSuite, Adaptive Insights and Zendesk.
5. Source control using Git.
6. Scripting using Python.
7. Modeling using dbt.Python
8. Git or GitHub
9. dbt

Systems/Tools we use:

1. GTM and Revenue: Marketo, Salesforce, NetSuite, Adaptive Insights, Zendesk
2. Product / User Analytics: GA360, Pendo
3. Data Engineering: dbt, Fivetran, Dagster, Airflow, Python
4. Business Intelligence, Data Modeling & Querying: dbt, SQL, Tableau, DataGrip
5. Data Storage & Compute: AWS Redshift, AWS S3, Databricks
6. Project Management & Documentation: Jira, Confluence

Skills

• Analytical Thinking
• AWS
• Database Management
• Operations
• Python
• SQL