The Role
Own an analytics project for go-to-market teams by combining CRM, campaign, and account data with SQL and Python. Build reusable data models, define acquisition and pipeline metrics, investigate data quality issues, add validation checks, and create dashboards and analyses. Communicate findings, recommendations, assumptions, and limitations to stakeholders while documenting reproducible workflows.
Summary Generated by Built In
Why Join Us
Tractian combines hardware, software and AI to help industrial teams detect equipment problems early and prevent costly downtime. Our technology supports more than 3,761 plants and monitors over 370,000 industrial assets. As a Y Combinator company, we’ve been recognized on the Forbes AI 50, named a G2 Leader and ranked No. 24 on Deloitte’s Technology Fast 500 in North America. Join us to help build technology that keeps industry running.
GTM Analytics at Tractian
Our go-to-market teams use data to understand how we attract customers and turn interest into sales. GTM Analytics builds the data models and analyses behind those decisions, using SQL and Python to investigate performance and test assumptions. The goal is to give our teams reliable evidence for where to focus and what to improve.
What You Will Do
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.
Responsibilities
- 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.
Requirements
- 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.
Helpful Experience
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.
What You Will Gain
- 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.
Skills Required
- Currently pursuing Engineering, Business Analytics, or a related quantitative field.
- Strong SQL skills, including joins, aggregations, and window functions.
- Proficiency in Python for data processing and automation.
- Experience building a data project through coursework, research, an internship, or independent work.
- Ability to organize data, check data quality, and make analysis reproducible.
- Ability to turn business questions into analytical approaches and explain findings and limitations.
- Ownership of work, including investigating unexpected results and improving approaches through feedback.
- Experience with data warehouses, Databricks, or PySpark.
- Experience with ETL or ELT workflows, Git, BI tools, or HubSpot data.
- API integration experience and familiarity with sales funnels.
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The Company
What We Do
Tractian is a machine-intelligence company delivering integrated hardware, cloud software and AI to prevent machine failures and boost industrial uptime. Their offering combines vibration and condition sensors, TracOS maintenance-management software, and AI-driven analytics to enable predictive maintenance, energy optimization and operational visibility for factories and asset-heavy operations globally.
