Company: Officeworks

Job Type: Full-Time

Work Mode: Hybrid / On-Site (Based on Business Requirements)

Experience Required: 5+ Years

Salary: 7 LPA – 10 LPA

Why this role exists:

The Data Scientist is a key member of the Advanced Analytics team, responsible for the end-to-end delivery of advanced analytics projects. The role partners with various business functions to understand requirements and develop the analytic methods and algorithms necessary to support data-driven decision-making across the organization.

Where you will make a difference:

In this role you will:

Data Science and Model Development:

• Develop, test and improve statistical, machine learning and optimization models to solve priority business problems.
• Apply appropriate data science techniques such as regression, classification, clustering, forecasting, segmentation, experimentation, optimization and recommendation models.
• Use programming tools such as Python, R and SQL to prepare analysis, build models and evaluate model performance.
• Select fit-for-purpose modelling approaches based on the business problem, data quality, interpretability needs and implementation pathway.
• Document model assumptions, methodology, limitations and performance so outputs are transparent and reusable.

Use Case Shaping and Analytical Problem Solving:

• Work with Analytics Business Partners, Business Analysis & Process Improvement roles and business stakeholders to understand the business problem, decision need and expected outcome.
• Help assess whether data science is the right approach for a business problem, or whether simpler analysis, reporting or process improvement is more appropriate.
• Translate business questions into testable hypotheses, modelling approaches and success measures.
• Support opportunity sizing, scenario analysis and analytical design for priority initiatives and cross-functional squads.
• Provide technical input into feasibility, data requirements, delivery risks and expected model value.

Squad and Enterprise Support:

• Support squads, projects and enterprise initiatives by providing data science expertise where advanced modelling or analytical methods are required.
• Partner with Data Analysts to ensure model outputs are interpreted clearly and linked to business decisions.
• Partner with Analytics Engineers and Data Engineers to ensure the data required for modelling is available, fit for purpose and well understood.
• Work with AI Engineers or technical teams where models need to be integrated, automated or scaled into business processes.
• Support transition of models into BAU with clear documentation, monitoring requirements and ownership arrangements.

Model Quality, Decision Support and Responsible Use:

• Validate and monitor model performance using appropriate statistical, technical and business outcome measures.
• Ensure models are explainable, reliable and fit for the decisions or business processes they support.
• Document model methodology, assumptions, limitations, risks and recommended use.
• Translate model outputs into clear insights, recommendations and practical decision support.
• Use visualization and storytelling to explain patterns, trade-offs and expected business impact.
• Support business teams to understand how model outputs should be used, including where human judgment or review is required.
• Apply privacy, security, governance and responsible AI principles throughout the data science lifecycle.

Process & Continuous Improvement:

• Deliver projects using Agile methodologies, ensuring iterative value delivery and alignment with evolving business needs.
• Maintain a proactive problem-solving attitude, seeking to constantly improve the effectiveness of analytical models and workflows.
• Stay updated on industry trends and emerging technologies to keep Officeworks’ analytical capabilities competitive.

Who you will be working with:

• Internal Delivery Teams: Data Engineers, Analytics Leads, and Business Analysts.
• Internal Partners: Senior leaders and teams across Finance, Merchandise, B2B, Supply Chain, Marketing, Property, Store Operations, and People.
• External Partners: Third-party analytical support providers.

What success looks like:

• Actionable Insights: Business functions are successfully making decisions driven by data insights and advanced algorithms.
• Model Performance: Statistical models and machine learning algorithms are accurately predicting or solving business use cases.
• Seamless Integration: Analytics products are successfully implemented and adopted within the target business functions.
• Operational Quality: Solutions meet high quality-control standards through robust testing and QA processes.

How you will lead:

Individual Contributor:

• Lives our Officeworks values and behaviors
• Proactively contributes to a safe working environment, escalates appropriately if there are unsafe conditions or inappropriate behavior
• Operates in line with applicable Officeworks company policies and Code of Conduct
• Demonstrates a strong sense of personal accountability and curiosity to learn and develop

Qualifications and work experience:

Essential:

• Education: Bachelors degree in Mathematics, Applied Mathematics, Statistics, Physics, Computer Science, or a related field.
• Experience: 5+ years of experience in complex data science and analytics environments.
• Technical Expertise: Deep knowledge of machine learning algorithms (GLM, Neural Networks, etc.) and proficiency in R, Python, and SQL.
• Platform Knowledge: Experience working within AWS compute and analytics platforms.
• Communication: Exceptional verbal and written communication skills with the ability to present complex data to non-technical stakeholders.

Preferred:

• Visualisation: Strong skills in using PowerBI, Tableau, or similar visualisation tools.
• Agile: Experience delivering data science solutions within an Agile framework.
• Retail Context: Experience applying data science within a large-scale retail or omnichannel environment.