Description review
Software Engineer I
Precursory · Australia · back to the listing
HR standards
62/100
needs work
Title ↔ description
78/100
solid
Reads as
Data Engineer
82% confident
How others title the same work
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What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
About Precursory
Precursory is a risk intelligence and risk-transfer platform for freight operations. We ingest operational data from across the logistics supply chain — TMS records, telematics feeds, rate confirmations, dispatch systems — and turn it into models that price and transfer risk. We are building risk products for a supply chain that has never had risk priced against real operational signal. Learn more at .
The Role
We're hiring a Software Engineer I to work with the data our platform ingests and to help build and enhance the risk and prediction models that sit on top of it. You'll write the pipelines that clean and normalize messy freight data, build the features those models depend on, and ship the services that put model output in front of customers.
You'll see a problem from raw data through to production, and the work you ship in your first few months will be running against real freight and real policies. You'll have a senior engineer close by for review and pairing, and we expect you to ask a lot of questions early.
We care more about how you think than what you've already built. If you're a strong engineer early in your career who wants to learn an entire domain rather than a single service, this is a good fit.
What You'll Do
• Build and maintain ingestion pipelines for freight operational data from TMS platforms, telematics providers, and carrier systems.
• Write the transformation and validation logic that turns inconsistent, real-world records into data our models can use.
• Develop and improve features for our risk and prediction models, and help evaluate how those models perform.
• Build backend services and APIs that expose model output to customers and internal tools.
• Investigate data quality problems and model failures.
• Participate in code and design reviews, and contribute to how we test and monitor what we ship.
What We're Looking For
• 0–2 years of professional software engineering experience, or equivalent through internships and substantial personal or academic projects.
• Solid programming fundamentals in Python, or another language with a willingness to work primarily in Python.
• Comfort with SQL and relational data modeling.
• Clear written communication. Much of the work involves explaining what the data shows to people who aren't engineers.
• Curiosity about the problem domain, and comfort working without a fully specified answer.
• Bachelor's degree in Computer Science or a related field, or equivalent experience.
Nice to Have
• Experience in statistics, machine learning, or applied modeling.
• Experience with AWS or GCP.
• Any prior exposure to logistics, freight, insurance, or another operationally messy domain.
Originally posted on Himalayas
Precursory is a risk intelligence and risk-transfer platform for freight operations. We ingest operational data from across the logistics supply chain — TMS records, telematics feeds, rate confirmations, dispatch systems — and turn it into models that price and transfer risk. We are building risk products for a supply chain that has never had risk priced against real operational signal. Learn more at .
The Role
We're hiring a Software Engineer I to work with the data our platform ingests and to help build and enhance the risk and prediction models that sit on top of it. You'll write the pipelines that clean and normalize messy freight data, build the features those models depend on, and ship the services that put model output in front of customers.
You'll see a problem from raw data through to production, and the work you ship in your first few months will be running against real freight and real policies. You'll have a senior engineer close by for review and pairing, and we expect you to ask a lot of questions early.
We care more about how you think than what you've already built. If you're a strong engineer early in your career who wants to learn an entire domain rather than a single service, this is a good fit.
What You'll Do
• Build and maintain ingestion pipelines for freight operational data from TMS platforms, telematics providers, and carrier systems.
• Write the transformation and validation logic that turns inconsistent, real-world records into data our models can use.
• Develop and improve features for our risk and prediction models, and help evaluate how those models perform.
• Build backend services and APIs that expose model output to customers and internal tools.
• Investigate data quality problems and model failures.
• Participate in code and design reviews, and contribute to how we test and monitor what we ship.
What We're Looking For
• 0–2 years of professional software engineering experience, or equivalent through internships and substantial personal or academic projects.
• Solid programming fundamentals in Python, or another language with a willingness to work primarily in Python.
• Comfort with SQL and relational data modeling.
• Clear written communication. Much of the work involves explaining what the data shows to people who aren't engineers.
• Curiosity about the problem domain, and comfort working without a fully specified answer.
• Bachelor's degree in Computer Science or a related field, or equivalent experience.
Nice to Have
• Experience in statistics, machine learning, or applied modeling.
• Experience with AWS or GCP.
• Any prior exposure to logistics, freight, insurance, or another operationally messy domain.
Originally posted on Himalayas