Acuity Analytics

Design and build scalable data product foundations including pipelines, quality systems, and ML-assisted solutions, while troubleshooting and operationalizing evaluation frameworks. | 5+ years in data science, data engineering, or ML engineering with strong Python, SQL, and production experience deploying LLMs and data tooling. | Please note: this role requires working in US time zones. About Us Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations. To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency. About the role You’ll work at the intersection of data science, data engineering, AI engineering, and operations, embedded closely with our DaaS Delivery Operations team and cross-functional stakeholders. You’ll design and build the technical foundations that power our data products—developing data pipelines, quality systems, evaluation frameworks, and ML-assisted solutions that directly improve delivery outcomes and operational efficiency. This role is highly execution-focused and ideal for someone who enjoys building end-to-end systems, solving complex data and ML problems in production environments, and working closely with delivery teams to unblock work through strong technical implementation. You should be comfortable owning solutions from design through deployment and iteration, with minimal reliance on hand-offs. Skills and Experience required 5+ years in data science, data engineering, or ML engineering roles Strong proficiency in Python and SQL Hands-on experience with data tooling (pandas, Plotly, Streamlit, Dash) Practical experience working with LLMs and deploying ML solutions in production environments Experience integrating and working with APIs and technical systems Strong problem-solving skills with a bias toward implementation and delivery Excellent collaboration and communication skills in cross-functional teams What you will do Data Systems & Delivery Engineering Build and maintain scalable data pipelines and transformation workflows Implement data quality checks, validation frameworks, and monitoring systems Design and operationalize evaluation frameworks for datasets and ML outputs Package and deliver production-ready datasets with clear documentation and QA standards ML & AI Enablement Develop ML-assisted tools and workflows to improve data processing and delivery efficiency Generate, augment, and validate synthetic datasets to support client and internal use cases Deploy lightweight ML/LLM-powered solutions to solve operational bottlenecks Improve automation and repeatability across data workflows Delivery Engineering & Technical Operations Work directly with delivery teams to implement and maintain production workflows Debug, troubleshoot, and resolve technical issues across data pipelines and systems Continuously improve tooling, processes, and measurement approaches used in delivery Identify and implement practical improvements that increase speed, reliability, and quality of delivery outcomes Why join us People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive. Check out this page for more details. If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics. For more details about life at Ascent, check out our Life Page here. For more details about Acuity Analytics please see here: Read here.

Design and maintain a centralized reporting platform using Power BI and Azure Databricks for claims reporting transformation. | Strong hands-on experience with Power BI, DAX, Azure Databricks, PySpark or Spark SQL, and data warehousing principles with large datasets in an international setting. | Please note this role must be based in Malta or Bulgaria. The creative mind behind every project. Put your skills to the test to build solutions that continue to shape the world we live in! About Us Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations. To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency. About the Role We are seeking a (Senior) BI & Data Engineer – Power BI & Azure Databricks to support a global reinsurance client in transforming their claims reporting landscape. You will play a key role in building and operating a centralized reporting platform, contributing to the development of a single source of truth for claims data on Azure Databricks. This role combines strong Power BI expertise with hands-on data engineering skills, enabling you to design scalable data models, deliver high-quality dashboards, and ensure robust, performant, and business-aligned reporting solutions. You will work closely with stakeholders across business and technology to translate complex reporting needs into impactful analytics products. Key Responsibilities Power BI & Analytics Design, develop, and maintain Power BI datasets, semantic models, and reports for global claims reporting Implement best-practice data modelling (star schema, claim-centric fact tables, conformed dimensions) Develop complex DAX measures for claims KPIs (e.g. incurred, paid, reserves, ultimates, movements) Optimise report performance (model size, DAX efficiency, incremental refresh) Ensure consistency of KPIs and definitions through a centralized data model Databricks & Data Engineering Work with Azure Databricks (Delta Lake) as the primary reporting data source Contribute to the design and implementation of curated data layers (e.g. silver/gold) Develop and maintain SQL / Spark-based transformations aligned with reporting requirements Support data quality, reconciliation, and traceability from source systems to reporting outputs Collaborate with data product teams and follow platform standards and governance Collaboration & Delivery Work closely with Product Owners, stakeholders, and cross-functional teams Translate business reporting requirements into scalable technical solutions Contribute to agile delivery (backlog refinement, sprint execution, documentation) Promote knowledge sharing and best practices within the team Required Skills & Experience Strong hands-on experience with Power BI (data modelling, DAX, performance optimisation) Proven experience building enterprise-grade dashboards and semantic models Practical experience with Azure Databricks (PySpark and/or Spark SQL) Solid understanding of Delta Lake and medallion architecture Strong grounding in data warehousing and BI architecture principles Experience working with large, complex datasets in a reporting environment Ability to work independently in a multi-stakeholder, international setting Nice to Have Experience in insurance or reinsurance reporting Familiarity with claims data (losses, reserves, payments, ultimates, movements) Knowledge of data governance, data products, or data mesh concepts Experience with financial or actuarial reporting Exposure to DevOps / CI-CD for Power BI or Databricks Understanding of regulatory or management reporting in insurance Why join us People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive. Check out this page for more details. If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics. For more details about life at Ascent, check out our Life Page here. For more details about Acuity Analytics please see here: Read here.