Advanced Analytics Engineer

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🕒 April 1

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Augusta Hitech

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Augusta Hitech is an innovative technology company that offers a comprehensive range of services to address complex technology needs for businesses. Their expertise includes managed services, AI-powered solutions, enterprise systems, quality engineering, and cloud infrastructure. They provide professional services such as staff augmentation to deliver engineering talent and offer extensive SAP Implementation & Integration Services ensuring smooth and efficient business operations. Augusta Hitech's proprietary AI technology, SecQ AI, simplifies and automates customer security reviews. They hold ISO 90001:2015 and ISO 27001 certifications, emphasizing their commitment to quality and security standards. The company is heavily involved in data science and the application of AI and deep learning in various industry use cases.

📋 Description

• Build foundational analytical constructs in Python • Develop reusable Python modules that transform structured datasets into analytical building blocks used across the platform • Create structured analytical outputs that AI systems can reliably interpret • Develop analytical tools that allow the platform’s conversational interface to answer data questions reliably • Collaborate with data platform teams to consume structured datasets from environments such as Databricks • Implement validation logic to ensure analytical outputs reconcile with underlying datasets • Design analytical outputs that maintain clear traceability between source data, analytical computations, and AI-generated explanations

🎯 Requirements

• Extensive experience building production-grade Python systems that analyse structured datasets • Strong SQL skills for working with relational datasets (e.g., Databricks) • Experience building analytical computations such as aggregations, comparisons, trend analysis or variance analysis • Ability to design clear and reusable analytical code structures • Comfortable using Excel to articulate analytical concepts to business users • Experience working with financial or insurance datasets is nice to have • Familiarity with hierarchical or reporting datasets is nice to have • Experience integrating with modern data platforms (e.g. Databricks, Snowflake, BigQuery) is nice to have • Experience preparing structured data for machine learning or AI systems is nice to have • Familiarity with causal discovery approaches or graph-based relationship modelling is nice to have