Job Location: Gurgaon
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:
– Bachelor- s/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.
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