This role is ideal for someone who enjoys solving real-world problems using machine learning, statistical modeling, and business intelligence. Youll collaborate with actuaries, underwriters, and technical teams to integrate data science into core business processes. If youre looking to grow your career in a dynamic, data-rich environment, this is the role for you. Key Responsibilities: Insightful Analytics Analyze complex datasets to uncover trends, correlations, and actionable insights that inform business decisions Predictive Modeling Develop and operationalize machine learning models to improve forecasting, risk assessment, and customer engagement Scalable Data Infrastructure Build and maintain robust data pipelines for processing structured and unstructured data efficiently Business Intelligence Solutions Design and implement BI dashboards and reporting tools using the Microsoft BI stack and cloud platforms Cross-Functional Collaboration Work closely with actuaries, underwriters, and business stakeholders to embed data science into operational workflows Process Automation Automate recurring data processes and monitor performance to ensure reliability and scalability Technical Excellence Maintain high standards in coding, documentation, and testing across analytics and reporting platforms Job Experience and Skills Required: Bachelors degree or diploma in Informatics, Computer Science, Statistics, Mathematics, or IT Minimum 4 years experience in data science or analytics, preferably in insurance Proficiency in Python, R, Java, C++, C#, and SQL (T-SQL) Experience with Power BI, Azure Data Factories, Azure Synapse Analytics Strong understanding of statistical concepts, machine learning, and data modeling Excellent communication and problem-solving skills Apply now!

A leading financial analytics firm is looking for a talented and detail-oriented Junior Data Scientist to join their dynamic team. This is an excellent opportunity for someone passionate about applying data science to real-world financial challenges. In this role, youll contribute to building predictive models, automating data insights, and developing robust data pipelines to support initiatives such as fraud detection, client churn analysis and portfolio optimization. Duties: Data Exploration & Management: Collect, clean, and prepare structured and unstructured financial data (e.g., client transactions, market prices, and investment flows). Assist with preparing, cleansing, and transforming data for the BI environment, ensuring data quality and consistency. Model Development: Support the development of machine learning models. Help evaluate model performance, document outputs, and improve feature engineering. Implement anomaly detection models across business units. Reporting & Visualization: Create reports (Power BI) to communicate findings to stakeholders. Collaboration: Work closely with different teams to understand their data needs and provide data-driven insights. Partner with Data Engineers, Analysts, and business stakeholders to ensure that analytical outputs are relevant and actionable. Contribute to internal automation, reconciliation, and alerting tools to streamline operations. Job Experience and Skills Required: Bachelors Degree in Data Science, Statistics, Finance, Economics, Computer Science, or a related field. Minimum of 0-2 years of experience in data analysis within the finance industry. Proficient in Python, including libraries such as pandas, matplotlib, and scikit-learn. Experience with Power BI, Excel, and other reporting tools. Experience in writing basic SQL queries. Knowledge of financial databases and platforms. Understanding of data pipelines, version control using Git, and cloud-based environments is advantageous. Apply now!