Job Description
I am currently partnering with an innovative technology company to find a Senior Data Scientist. This is a critical role for an experienced practitioner with a strong quantitative foundation and a proven track record of solving complex measurement and forecasting problems in production.
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Working closely with my client's leadership, you will own the end-to-end modelling lifecycle — from architecting solutions and translating ambiguous business problems into statistical frameworks, to deploying robust models and communicating strategic insights to the executive team.
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My client is looking for someone who brings years of industry experience and a pragmatic approach to data science ( Retail or Ecom) You will need sharp statistical fundamentals, strong engineering habits, and the ability to act as a technical leader within the business—instinctively stress-testing results, establishing best practices, and elevating the capabilities of the wider team.
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What You'll Do
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Architect and Lead: Design, build, and deploy robust statistical and machine learning models for forecasting demand and core business metrics (e.g., regularised regression, gradient boosting) while ensuring interpretability (e.g., SHAP).
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Own Causal Inference: Lead the incrementality measurement strategy—designing complex experiments, advanced A/B testing frameworks, matching methods, and synthetic controls.
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Advanced Forecasting: Implement and scale time-series methods, including Bayesian Structural Time Series (BSTS), to estimate incremental impact and forecast against a credible baseline.
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Strategic Partnership:



Partner closely with the company's business leaders to translate ambiguous goals into well-defined, measurable analytical projects.
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Technical Excellence: Write production-ready, highly reproducible analysis code. Drive data science best practices across the team, including version control, CI/CD, and MLOps workflows.
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Stakeholder Management: Communicate complex statistical findings and their strategic implications clearly and persuasively to non-technical executives.
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Mentorship: Mentor junior team members, guiding them on statistical rigour, engineering standards, and practical problem-solving.
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What My Client is Looking For
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Background You're likely a strong fit if you possess:
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5+ years of industry experience as a Data Scientist, with a strong focus on forecasting, causal inference, and machine learning.
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A relevant quantitative degree (e.g., Data Science, Statistics, Mathematics, Computer Science, Econometrics). An advanced degree (Master's or PhD) is highly regarded.
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Required Skills
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Expert-level Statistics & Probability: Deep expertise in reasoning about uncertainty, experimental design, and hypothesis testing in real-world, noisy environments.
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Advanced Coding: Expert proficiency in Python and SQL for complex data manipulation, modelling, and productionizing workflows.
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MLOps & Engineering: Strong understanding of how to put models into production, including monitoring for drift, train/test discipline, and model lifecycle management.
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Executive Communication: Exceptional written and verbal communication skills—you can explain complex methodologies and their limitations to a non-technical audience with ease.
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Strong Pluses
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A proven track record of implementing advanced causal inference, econometrics, or Bayesian time-series forecasting (e.g., BSTS) in production environments.
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Extensive experience with modern data stacks (e.g., Snowflake, dbt), cloud platforms (AWS/GCP/Azure), and orchestration tools.
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Experience leading or scaling a data science function within a fast-paced technology, digital platform, or B2B SaaS environment.
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What My Client Offers
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High Impact & Autonomy: Ownership of critical technical capabilities where your work directly drives the company's strategy.
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Leadership Opportunities: The chance to shape the technical direction of the team and mentor junior data scientists.
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Technical Collaboration: Work alongside highly experienced data engineers and scientists in a mature data environment.
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Benefits: A highly competitive salary, dedicated learning and development budget, adaptable/hybrid working, generous leave policies, and more.
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📌 Senior Data Scientist (New South Wales)
🏢 Sirius.
📍 New South Wales