Job Description

Job Description Sutherland is seeking an organized and reliable person to join us as a Manager Data Science . We are a group of driven and supportive individuals. If you are looking to build a fulfilling career and are confident you have the skills and experience to help us succeed, we want to work with you! Manager Responsibilities: Data Analytics and Insights: Conduct analytics to identify patterns and generate actionable insights to support strategic decisions. Process Unstructured data to drive actionable insights. Translate quantitative analyses into comprehensive visuals and reports for non-technical audiences. Model Development and Validation: Build, validate, measure, and retrain machine learning models, including supervised and unsupervised algorithms. Apply expertise in Natural Language Processing (NLP) and Generative AI to solve complex business challenges. Deployment and Collaboration: Collaborate with AI Engineers to deploy machine learning models and set up inference processes. Ensure models are scalable, maintainable, and aligned with organizational goals. What Will you focus on : Risk Assessment and Pricing : Developing predictive models to evaluate risks and set accurate premiums. By analyzing historical data, they identify patterns that inform underwriting decisions. Fraud Detection : Implementing machine learning algorithms to detect fraudulent activities by identifying anomalies in claims data. This proactive approach helps in minimizing losses due to fraud. Customer Segmentation and Personalization : Analyzing customer data to segment the market and tailor insurance products to specific groups, enhancing customer satisfaction and retention. Claims Management Optimization : Utilizing data analytics to streamline the claims process, ensuring timely and accurate settlements. This includes predicting claim volumes and identifying potential bottlenecks. Marketing Strategy Enhancement : Assessing the effectiveness of marketing campaigns and identifying opportunities for customer acquisition and retention Requirements: Experience: 6-7 years of experience in Insurance analytics or a related domain Education: bachelors degree in Engineering, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in programming languages and data analysis tools such as Python, R, PySpark, and SQL. Solid experience in developing predictive modelling techniques (look-a-like models, time series forecasting, regression, clustering) Ability to design, implement, and refine business rules for optimizing the Claims and Underwriting value chains is a good to have. Familiarity with working in cloud environment (AWS/ AZURE), using distributed compute for large datasets, and version control tools (eg Git) Data Proficiency: Expertise in handling large-scale Insurance datasets and applying statistical and machine learning methods to drive actionable insights. Data Storytelling & Communication: Demonstrated ability to translate complex data insights into clear, compelling narratives and presentations. Adept at communicating technical findings in a relatable manner to non-technical stakeholders. Autonomy & Prioritization: Proven ability to work independently, manage multiple projects/workstreams, and prioritize effectively in a fast-paced, data-driven environment. Problem-Solving & Collaboration: Demonstrated ability to troubleshoot complex data issues, optimize system performance, and work effectively within a team environment.