Job Description
<p><p><b>Silicon Stack</b> is a leading Australian software development and consulting company headquartered in Melbourne, serving a global clientele across Australia, New Zealand, Europe, North America, UK, and Asia.<br/><br/> Renowned for our "can-do attitude" and proven track record, we deliver high-quality solutions with expertise in cutting-edge technologies.<br/><br/> We excel in functionality, aesthetics, and Responsibilities :</b></p><p><br/> - Design and implement causal inference and incrementality models, such as randomized holdouts, synthetic control, uplift regression, and time-series forecasting.</p><br/> - Develop profitability and ROI models at the SKU, product, and customer levels applicable to retail media, CRM campaigns, and financial forecasting.<br/><br/> - Automate and maintain robust data pipelines using SQL, Python, and R to unify data across systems like Amazon Ads, Salesforce, Adobe Analytics, SAP, and CRM databases.<br/><br/> - Conduct ad-hoc statistical analyses and simulations, including A/B testing, media mix modeling, and customer journey analytics.<br/><br/> - Partner with Finance, Marketing, and Operations teams to translate analytical insights into strategic business recommendations.<br/><br/> - Mentor junior analysts, ensuring the use of rigorous statistical methodology and scalable model Skills & Experience :</b><br/><br/> - 5 to 7+ years of experience in Data Science or Advanced Analytics.<br/><br/> - Proficient in Python and R, including libraries such as statsmodels, scikit-learn, Prophet, and causal inference packages.<br/><br/> - Advanced SQL skills for data wrangling, query optimization, and ETL workflows.<br/><br/> - Hands-on experience with incrementality testing, campaign attribution, and ROI modeling (e.g., for retail media or CRM).<br/><br/> - Familiarity with marketing and enterprise tools: Adobe Analytics, Salesforce (SFDC), SFMC, SAP, Google Ads, Meta Ads.<br/><br/> - Strong business acumen in profitability analysis, marketing ROI, and P&L impact.<br/><br/> - Exceptional communication and stakeholder engagement Qualifications :</b></p><br/> - Experience working with large-scale marketing datasets and customer lifecycle analytics.<br/><br/> - Exposure to cloud platforms and data engineering tools (e.g., AWS, GCP, Airflow, dbt).<br/><br/> - Understanding of privacy-first analytics and data governance in marketing tech stacks.</p><br/></p> (ref:hirist.tech)