# Senior Associate - AI / Data **Company**: Davies **Location**: Viman Nagar, Maharashtra **Work arrangement**: onsite **Experience**: senior **Job type**: full-time **Category**: Data Science **Industry**: Consulting **Apply**: https://davies.pinpointhq.com/en/postings/8fcfd733-209c-437a-84b7-3ce9760319aa?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_24b86ef7-215 ## Description As a Senior Associate - AI / Data at Davies, you will collate, model, and interpret complex data to deliver business-focused insights and applied science solutions across the claims lifecycle and broader professional services operations. You will work across the full data science pipeline , from data assembly and feature engineering through to model development, validation, and deployment , partnering with stakeholders across the Group to turn data into measurable business value. ## Key Responsibilities - Assemble, cleanse, and model large, complex datasets from across the Group to meet functional and non-functional business requirements, using the medallion architecture on the Davies Microsoft data platform (Azure Data Factory, Microsoft Fabric, and Power BI). - Design, build, and validate statistical and machine learning models for business-focused use cases including claims triage, fraud detection, outcome prediction, and operational efficiency optimisation. - Collect and structure data through a combination of business analysis, study design, and automated collection pipelines , identifying the most valuable signals within large, complex datasets. - Build and maintain analytical tools and reporting solutions that provide stakeholders with actionable insight into key business performance metrics, including operational efficiency, claims outcomes, and customer experience. - Create clear, compelling reports, dashboards, and presentations that translate complex data findings into simple, actionable recommendations for business, product, and executive audiences. - Develop and implement experimental frameworks for data collection and model evaluation, including A/B testing, model validation, and performance monitoring in production environments. - Partner with data engineers, AI engineers, and platform teams to ensure data science outputs are production-ready, well-documented, and integrated effectively into Davies systems and workflows. - Work with stakeholders across data, product, design, and executive teams to understand their data science needs, define problem statements clearly, and deliver solutions that are technically rigorous and practically useful. - Contribute to the continuous improvement of data science practice at Davies, including tooling, methodology, model governance, and knowledge sharing across the AI Office and wider Group. ## Skills, Knowledge & Expertise - Proficiency in Python and/or R for data analysis, statistical modelling, and machine learning, with strong command of relevant libraries (pandas, scikit-learn, PyTorch, or equivalent). - Hands-on experience with the Microsoft data platform, including Azure Data Factory, Microsoft Fabric, and Power BI, for data ingestion, transformation, and visualisation. - Experience designing and evaluating machine learning models , including classification, regression, clustering, and NLP techniques , and deploying them in production or near-production environments. - Strong SQL skills and experience working with relational databases, data warehouses, and medallion architecture data lake patterns. - Ability to visualise and communicate complex data in the most effective way possible , matching chart type, narrative, and level of detail to the audience and business question. - Excellent written and verbal communication skills, demonstrated through the preparation of reports, presentations, and technical documentation for diverse audiences including senior leadership. - Analytical and problem-solving mindset with exceptional attention to detail , comfortable searching through large, messy datasets to surface usable and statistically meaningful insight. - Ability to work independently and collaboratively across teams with different technical backgrounds, translating between data science concepts and business requirements with clarity. - Experience building data transformation processes that handle workload management, data structures, dependencies, and metadata in a governed, repeatable way. - Familiarity with model monitoring, experiment tracking, and MLOps principles , ensuring that models remain performant and auditable over time. - Continuous improvement mindset, naturally inquisitive and intellectually driven, with a passion for finding signal in data and translating it into business impact. - Experience applying data science in insurance, financial services, claims management, or other regulated industries is a strong advantage, particularly where data governance and model explainability are key requirements. - Familiarity with AI and generative AI tooling , including LLMs, embedding models, and vector search , and an interest in how classical data science and modern AI methods can be combined to deliver greater business value is an advantage. ## Skills ### Required - Python - R - Microsoft data platform - Azure Data Factory - Microsoft Fabric - Power BI - SQL - Machine Learning - Data Analysis - Statistical Modelling - Data Visualization - Communication - Problem-solving - Data Governance - MLOps ### Nice to have - Experience applying data science in insurance, financial services, claims management, or other regulated industries - Familiarity with AI and generative AI tooling — including LLMs, embedding models, and vector search --- Source: [Apply at davies.pinpointhq.com](https://davies.pinpointhq.com/en/postings/8fcfd733-209c-437a-84b7-3ce9760319aa?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)