[Hiring] Analytics Intern @Tractian

Role Description

Take ownership of a focused analytics project that helps our go-to-market teams answer a business question. You’ll use SQL and Python to combine data from different sources, investigate inconsistencies and build a reliable analysis. Explain what your findings support, where uncertainty remains and how the team can use the results.

• Write SQL transformations and Python workflows to combine CRM, campaign and account data into reliable datasets.
• Build reusable data models and define consistent metrics for customer acquisition and sales pipeline performance.
• Investigate missing records, duplicates and conflicting results. Add validation checks to catch errors before teams rely on the data.
• Work with GTM stakeholders to turn business questions into dashboards and analyses that inform decisions.
• Explain your findings and recommendations, including what the data cannot tell us. Document assumptions and how datasets and reports are updated.

Qualifications

• Engineering, Business Analytics or a related quantitative field.
• Strong SQL skills, including joins, aggregations and window functions, and proficiency in Python for data processing and automation.
• Experience building a data project through coursework, research, an internship or independent work. You should be able to explain how you organized the data, checked its quality and made your analysis reproducible.
• Ability to turn a business question into an analytical approach, explain your findings and recognize the limits of your conclusions.
• Ownership of your work, including investigating unexpected results and improving your approach through feedback.

Requirements

• Experience with data warehouses, Databricks or PySpark, ETL/ELT workflows, Git, BI tools or HubSpot data.
• API integration and familiarity with sales funnels are useful.

Benefits

• Hands-on experience using SQL and Python to solve a business problem with sales and marketing data.
• Feedback on your code, data models and analytical approach from the team.
• A deeper understanding of how customer acquisition and sales performance are measured.
• Practice presenting findings and recommendations to the people who will use them.