Data Scientist

This position is responsible for translating complex analytical concepts into actionable results for our clients.

- He/she will be involved in the development and execution of all data science activities relating to client specific projects.

- He/she will also be directly responsible for preparing, analyzing and generating effective project results in an efficient and errorless manner using statistics, optimization and machine learning techniques, delivered on time and on budget.

Primary Responsibilities:

- Conduct advanced predictive modeling projects around: Propensity Modeling, Time to Event Modeling, Recommendation Engine, Customer LTV, Market Mix, Text Mining and Social Media Analytics.

- Generate and execute required data science activities with minimal supervision.

- Leverage R, SAS, SQL & Excel to dig into data to extract meaning from information.

- Produce appropriate and effective project deliverables including: sample diagnostics, customer profiles, complex queries, datamining, model algorithms, gains charts, model score distributions, etc., with zero defect.

- Demonstrate a strong understanding of project scope, data extraction methodology, design of dependent and profile variables, logic and design of data cleaning, exploratory data analysis and statistical methods.

- Produce timely and error-free deliverables in an efficient manner, managing multiple tasks and varying project scopes.

- Manage data audit steps to ensure data quality.

Requirements for position:

- Education: MS/PhD in Statistics, Mathematics, Operations Research, Computer Science.

- Preferred disciplines of study include Statistics, Optimization, Machine Learning or Applied

- Mathematics

General Qualifications:

- At least 6 years of experience in following work areas:

- Predictive Modeling & Data Mining

- Competitive/Customer Intelligence

- Big Data and High Performance Computing

Related Knowledge Base:

- Ability to show value of analytics within business processes

- Strong R, SAS & SQL skills

- Regression (linear, logistic, multinomial, censored) , Survival Modeling, Segmentation and clustering, Decision tree analysis etc.

- Machine Learning Algorithms: Neural Networks, SVM, Bayesian Belief Net, Hidden Markov Models,etc.

- Mathematical programming and optimization

- Ability to interpret analytical results

- Strong verbal and writing skills

If interested forward CV with following details:

Years of Experience:
Relevant experience:
Current CTC:
Expected CTC:
Joining Time: