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Data Solutions Analyst / Scientist

Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full-Time
From the employer’s posting

What you’ll work on

Full posting

You will lead the development and continuous improvement of forecasting solutions that support both operational execution and long-term network strategy.

Working with large, complex datasets, you’ll build and manage models that inform everything from daily planning decisions through to multi-year volume forecasts and network optimisation.

  • Lead end-to-end network forecasting across first, middle and last mile

  • Enhance short- and long-range volume forecasts

  • Build scenario models and sensitivity analysis for planning under uncertainty

  • Design scalable, analytics-ready datasets and forecasting pipelines

  • Translate complex forecast outputs into decision-ready insights

From the employer’s posting
You will lead the development and continuous improvement of forecasting solutions that support both operational execution and long-term network strategy.
Working with large, complex datasets, you’ll build and manage models that inform everything from daily planning decisions through to multi-year volume forecasts and network optimisation.
Lead Network Operations end-to-end network forecasting across first, middle and last mile
Enhance short and long-range volume forecasts
Build scenario models and sensitivity analysis to support planning under uncertainty
Design and build scalable, analytics-ready datasets supporting forecasting and planning
Translate complex outputs into clear, decision-ready insights and narratives

What you’ll bring

All qualifications

Core experience

  • 5+ years’ experience in forecasting, data science or advanced analytics (ideally within logistics, supply chain or operations)
  • Strong experience building forecasting models using time series, regression or machine learning techniques
  • Experience working with large, complex, multi-source datasets
  • Experience with Python/R or forecasting tools (e.g.
  • Experience with analytics engineering practices (testing, Git, CI/CD workflows)
Qualification wording
5+ years’ experience in forecasting, data science or advanced analytics (ideally within logistics, supply chain or operations)
Strong experience building forecasting models using time series, regression or machine learning techniques
Experience working with large, complex, multi-source datasets
Experience with Python/R or forecasting tools (e.g. Prophet, ARIMA, XGBoost)
Experience with analytics engineering practices (testing, Git, CI/CD workflows)

About APG eCommerce Solutions

We’re seeking a Data Solutions Analyst / Scientist to lead forecasting, AI-driven models and scalable data products that support Australia Post’s national network operations.

In the employer’s words · Read in context

Posting record

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Status in our records
Live
First seen by us
Aug 14, 202683 days ago
Recorded sightings
45
Last seen by us
Nov 6, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 83

Up longer than most. Similar jobs usually come down between day 7 and day 56.

At APG eCommerce Solutions, jobs usually come down by about day 59.

From 10,398 similar postings that came down, and 5 of APG eCommerce Solutions’s. Coming down is not always a hire.

APG eCommerce Solutions is hiring

2 open jobs

  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • R
  • SQL
  • BigQuery
  • GCP
  • Looker
  • Tableau
  • XGBoost
Where the posting names them
- Advanced SQL capability and experience with cloud platforms (e.g. GCP, BigQuery) - Experience with Python/R or forecasting tools (e.g. Prophet, ARIMA, XGBoost) - Strong stakeholder engagement skills, with the ability to translate complex concepts into clear insights
- Design and build scalable, analytics-ready datasets supporting forecasting and planning - Develop production-grade data models and forecasting pipelines using SQL and cloud platforms such as GCP and BigQuery, with exposure to tools such as Dataform or Vertex AI highly regarded. - Apply analytics engineering practices (modelling, testing, CI/CD, version control)
- Willingness to learn and apply and showcase a challenging mind to improving forecasts and how they can be used in the business for commercial and service improvements - Advanced SQL capability and experience with cloud platforms (e.g. GCP, BigQuery) - Experience with Python/R or forecasting tools (e.g. Prophet, ARIMA, XGBoost)
- Experience with analytics engineering practices (testing, Git, CI/CD workflows) - Data visualisation and storytelling capability (e.g. Tableau, Looker) - Commercial acumen and an understanding of cost, service and capacity trade-offs

Your next step

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,818.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

JOB TITLE: Data Solutions Analyst/Scientist



REPORTS TO: Manager, Network Reporting



LOCATION: Amman, Jordan



Working hours: Flexible to accommodate Australian time zone



About the opportunity 

We’re seeking a Data Solutions Analyst / Scientist to lead forecasting, AI-driven models and scalable data products that support Australia Post’s national network operations. As part of the Network Insights, Analytics and Reporting team, you’ll own end-to-end network forecasting and partner with Operations, Planning, Finance, Commercial and Technology teams to deliver decision-ready insights. This high-impact role is ideal for someone who thrives in ambiguity, understands uncertainty, and can translate complex analytics into clear actions that improve service, cost, safety and network capacity outcomes.



About the role 

You will lead the development and continuous improvement of forecasting solutions that support both operational execution and long-term network strategy.  

Working with large, complex datasets, you’ll build and manage models that inform everything from daily planning decisions through to multi-year volume forecasts and network optimisation. 
 

 
What you’ll deliver 

Forecasting & strategic planning 

  • Lead Network Operations end-to-end network forecasting across first, middle and last mile and interconnections across our Enterprise forecasting analytical teams  
  • Enhance short and long-range volume forecasts so we can plan, execute and deliver beyond customer and commercial expectations 
  • Build scenario models and sensitivity analysis to support planning under uncertainty 
  • Integrate internal data with external drivers (economic, demographic, market trends) 

Stakeholder partnership & decision influence 

  • Partner with operations, planning and commercial teams to align forecasts to decisions 
  • Translate complex outputs into clear, decision-ready insights and narratives 
  • Influence trade-offs between cost, service, capacity and performance outcomes 
  • Build trust in forecasts through transparency, governance and consistency 

Advanced analytics & modelling 

  • Apply statistical, machine learning and AI methods where appropriate, including time series forecasting, regression, causal modelling, anomaly detection, classification and clustering. 
  • Continuously improve forecast accuracy, bias tracking and model performance 
  • Determine when advanced modelling adds value vs simpler approaches
     

Data & analytics engineering 

  • Design and build scalable, analytics-ready datasets supporting forecasting and planning 
  • Develop production-grade data models and forecasting pipelines using SQL and cloud platforms such as GCP and BigQuery, with exposure to tools such as Dataform or Vertex AI highly regarded. 
  • Apply analytics engineering practices (modelling, testing, CI/CD, version control) 
  • Ensure strong data governance, quality and documentation across forecasting pipelines
     

Commercial impact & continuous improvement 

  • Identify opportunities to improve cost efficiency, service outcomes and network performance 
  • Translate insights into actionable changes across planning and operations 
  • Champion a data-driven culture and continuous improvement
     

 

About you

  • 5+ years’ experience in forecasting, data science or advanced analytics (ideally within logistics, supply chain or operations) 
  • Strong experience building forecasting models using time series, regression or machine learning techniques 
  • Experience working with large, complex, multi-source datasets 
  • Willingness to learn and apply and showcase a challenging mind to improving forecasts and how they can be used in the business for commercial and service improvements 
  • Advanced SQL capability and experience with cloud platforms (e.g. GCP, BigQuery) 
  • Experience with Python/R or forecasting tools (e.g. Prophet, ARIMA, XGBoost) 
  • Strong stakeholder engagement skills, with the ability to translate complex concepts into clear insights 
  • Experience with analytics engineering practices (testing, Git, CI/CD workflows) 
  • Data visualisation and storytelling capability (e.g. Tableau, Looker) 
  • Commercial acumen and an understanding of cost, service and capacity trade-offs 
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Amman, Jordan

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