Analytics Manager/Data Scientist - Data Analytics & Solutions Team - Model Development Group

Department: Data Analytics and Solutions, Model Development

Requirements:

- Degree in Computer Science, Mathematics, Computational Linguistics, or similar field with experience in Machine Learning related projects with exposure to NLP. The ideal candidate would have 5+ years in similar roles

- Hands-on experience in various facets of ML techniques, such as supervised learning (decision tress, random forests, XGBOOST, and so on), semi-supervised learning, clustering, data discretization, normalization, sampling, classification, feature engineering, information extraction, structured prediction and ranking.

- Proven experience applying NLP research to real-world problems. Understanding of NLP techniques for text representation, extraction, data structures and modeling and developing NLP applications by finding and implementing the right algorithms.

- Programming skills in scripting languages e.g., Python or java or statistical packages e.g., R or similar

- Knowledge of statistics

- Familiarity with database management systems like SQL or PostgreSQL would be an added advantage

Job description 

We are seeking a data scientist to join our client's Data Analytics and Solutions team in the Model Development group. The team primarily focuses on modeling and developing data and applications related to insured property exposures.  The candidate would be engaged in the development, design, and implementation of a wide range of data products used in risk modeling, exposure modeling, valuation modeling, and Property & Casualty data quality assessment and enhancement. 

The candidate will be expected to gain and further utilize in-depth knowledge of the products and relevant technologies. The incumbent of this role will be primarily responsible for: 

- Researching and mining data from structured, semi-structured and unstructured sources to develop and improve our exposure data products 

- Developing and optimizing data collection systems using strategies that optimize statistical efficiency and quality 

- Applying machine learning techniques to develop and improve exposure and other data products 

- Identifying, analyzing, and interpreting trends or patterns in complex data sets using statistical techniques

- Working with stakeholders to gather understand and prioritize business and information requirements 

- Identifying and executing process improvement opportunities 

Other Skills: 

- Excellent written and verbal skills, as evidenced by white papers or technical presentations at meetings and conferences 

- Detail-oriented and self-driven individual 

- Outstanding analytical and problem-solving skills 

- Ability to independently scope, manage and drive projects