Sutherland - Manager - Data Science

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!

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.

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 modeling 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.

- 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