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Senior Data Scientist

Bapcor -
Mount Waverley VIC

Quick Apply

Job Details

Full-time

Benefits

Birthday leave
Parental leave
Paid volunteer leave

Qualifications

Power BI
Deployment
Bachelor's degree
Recruiting
AI
Analytics

Full Job Description

Company Description

Bapcor Ltd, the leading automotive aftermarket provider of accessories, equipment and service. We host one of the widest ranges of car parts in the world, with brands including Burson, Autobarn, Midas, Truckline, Premier Auto Trade and Baxters.

In joining our team, you’ll be welcomed into a supportive business that spans more than 1,000 locations with over 5,000 team members across Australia, New Zealand and Thailand. We are passionate about our team, with safety and inclusivity at the forefront of everything we do. We’re also passionate about our customers, products, and living our values of:

Doing the right thing
Being in it together
Giving a damn
Getting it done

Job Description

We’re looking for a Senior Data Scientist to build next‑generation analytics solutions using AI, machine learning, and data mining. You’ll work closely with business stakeholders to translate complex problems into clear technical hypotheses, develop accurate and scalable models, and embed them into impactful data products and tools. You’ll collaborate with a supportive, cross‑functional team to deliver insights that drive real business decisions.

What you’ll do

Partner with business stakeholders to develop innovative, data‑driven solutions using cutting‑edge analytics tools and techniques
Clearly communicate analytics approaches and outcomes, explaining how insights align with and support business objectives
Champion data‑driven decision‑making by educating stakeholders on the how and why behind analytical solutions
Lead analytical initiatives, working closely with data engineers, analysts, developers, and business leaders to integrate models into applications and tools
Design and build repeatable, interpretable, scalable models that are embedded into production‑ready analytics products
Engineer meaningful features using strong business acumen to improve model performance and interpretability
Share knowledge and passion for Data Science across the organisation, contributing to long‑term frameworks, standards, tools, and best practices

Qualifications

Bachelor’s degree with 5+ years’ experience in Data Science or a related field
Strong proficiency in Python, including hands‑on experience working with DataFrames
Proven experience applying Data Science techniques to large‑scale datasets, including: Machine learning for clustering, classification, regression, and anomaly detection
Optimisation or simulation techniques for prescriptive analytics
Experience visualising complex insights using tools such as Plotly, matplotlib, or ggplot2; dashboarding experience (e.g. Shiny, Dash, Power BI) is desirable
Demonstrated ability to generate new insights by merging, transforming, and analysing internal and external datasets
Exposure to Big Data and Cloud technologies such as Hadoop, Spark, H2O.ai, cloud‑based AI platforms, and containerisation is desirable
Experience supporting the deployment, monitoring, maintenance, and continuous improvement of analytical models is advantageous

Additional Information

At Bapcor, we focus on what matters most for our customers, team members and the communities we serve. We go the extra mile to get the job done and always live our values.

In joining our team, you can access:

Diverse career opportunities within the Bapcor Group
Discounts across Bapcor products and services, including our Retail and Trade brands
Industry leading policies to support your work/ life balance (gender neutral parental leave, purchase leave, volunteer leave etc…)
Paid birthday leave
Wellbeing support
Novated leasing and more

We pride ourselves on our inclusive work environment, and encourage applications from people of all ages, cultures, gender identity, abilities and backgrounds, providing a recruitment experience that’s fair, free from bias and accessible. If you need to inquire about reasonable accommodation for the application process, please email [email protected].

Quick Apply

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