Manager - Data Scientist - Insurance

Manager - Data Scientist/ NASDAQ Org.

Exp: 3 + Years

Role Overview:

- The person will be part of data science team for a major US insurance client.

- Doing independent research, analyze, and present data as assigned.

- Developing statistical models in SAS, Python/R.

- Develop detailed SAS/Python/R codes for data preparation and model scoring to be used in production.

- Critically examine and deep dive into models and improving model performance.

- Prepare detailed documentation of models output, performance and all the steps involved.

- Assist in learning and development of new team members.

- Identify and participate in continuous improvement initiatives.

Key Responsibilities:

- Complete understanding of business objective/problem statement as well as modeling goals.

- Experience in data extraction and data manipulation in SAS, Python/R and Excel.

- Data exploration, data preparation (outlier treatment, missing value imputation, variable transformation etc.), model building, model validation, optimization and scoring using SAS/Python/R.

- Preparing detailed documentation of models output results (of different iterations), model performance, feature importance and all the steps involved to optimize the model performance.

- Adhere to project deliverables and controls.

- Experience in data control and data automation.

- Good written and verbal communication skills.

Candidate Profile:

- Bachelors/Master's degree in computer science, mathematics, statistics.

- 2-7 years experience, preferably in data science/marketing analytics/building predictive models.

- Should be really proficient in building predictive statistical models (look alike/response models).

- Should have experience working on techniques like Logistic Regression, Decision Trees, Random Forest, GBM, XG-Boost, K-Means Clustering etc.

- Superior analytical and problem solving skills.

- Ability to take initiative, quick learner and innovative.

- Outstanding written and verbal communication skills.

- Able to work in fast pace continuously evolving environment and ready to take up uphill challenges.

- Is able to understand cross cultural differences and can work with clients across the globe.