Our client is looking for an innovative and commercially minded Data Scientist to design and implement AI and machine learning solutions that enhance HR and commercial decision-making. The successful candidate will work across advanced analytics, LLM-powered applications, semantic search, pricing analytics, anomaly detection, automation, and executive reporting solutions within a modern cloud-based analytics environment. This role combines AI innovation, machine learning engineering, analytics, and business intelligence to deliver impactful enterprise solutions. Requirements Key Responsibilities AI & Machine Learning Solutions Design and implement LLM-powered solutions for HR and commercial use cases. Develop intelligent automation solutions for: CV ingestion Candidate-to-role matching Semantic search capabilities Train, deploy, and manage ML models using MLflow. Analyse model performance and business impact. Advanced Analytics Develop advanced pricing and discount analytics models. Perform elasticity modelling and customer segmentation analysis. Conduct operations anomaly detection and proactive risk reporting. Build AI-driven survey analytics applications. Data Engineering & Governance Ensure pipelines are optimised, sustainable, and easy to debug. Implement data quality checks and governance processes. Monitor and improve operational analytics processes. Reporting & Visualisation Develop Power BI dashboards and executive-ready business insights. Translate complex datasets into strategic recommendations. Development & Collaboration Manage Git-based workflows including: Pull requests Branch syncing Merge conflict resolution Collaborate with technical and business stakeholders across HR, operations, and commercial teams. Monitor APIs and data integrations where required. Minimum Requirements Qualifications Degree in: Data Science Computer Science Statistics Mathematics Engineering or related field Experience 3–5 years’ experience in Data Science or Machine Learning roles. Experience building AI/LLM-powered solutions. Hands-on experience with MLflow and Databricks. Strong analytical and statistical modelling experience. Experience with Power BI and data visualisation. Exposure to semantic search and NLP solutions advantageous. Technical Skills Python SQL Databricks MLflow Power BI Machine Learning NLP / Semantic Search LLM Applications Git / Version Control API Monitoring Statistical Modelling Data Analytics & Reporting Advantageous Skills Azure AI Services Generative AI frameworks PySpark Customer Analytics Pricing Optimisation Models Cloud-based analytics platforms Soft Skills Strong commercial acumen Excellent analytical thinking Strong communication and presentation skills Problem-solving mindset Ability to work in fast-paced environments Strong stakeholder engagement abilities
Blue Pearl is a market-leading CLOUD Solutions developer with extensive knowledge and insight into the latest technologies, standardised processes, advanced technical capabilities and consulting processes available, ensuring wholistic success for our clientele. We offer professional consulting to compliment your business strategy and overall management and make it our priority to add value to any business by listening, analysing and creating a conducive solution that will empower our client.
We implement a Data Analysis Process that includes inspecting, cleansing, transforming, and modelling data with the end-goal of discovering useful information, informing conclusions, and relevant information to support your decision-making. Your business cannot afford not to engage with us, allowing our data analysis to play a role in making your business decisions more scientific and helping your business achieve effective operation.
Blue Pearl’s team of experts include BI strategists, BI analysts, Data Warehouse Architects, Data Scientists, Implementation and Development experts. With the use of BI, Analytics and Big Data, we effectively partner with our customers on their mission to achieve a competitive business advantage and real ROI from the structured information we collect.
