Cognilytics - Predictive Analytics/Modeler

Responsibilities:

- High energy player – must be motivated to perform and demonstrate excellence in understanding the business problem form client interactions, be innovative to create the analytical solution catering to the client problem and then deliver on the same.

- Should be dynamic and provide situational leadership : ready to perform both as an Individual contributor and Team Leader

- Holistic communication skills : verbal, written and creative

- The position will be responsible for developing analytics tools and techniques to solve business Problems.

- This involves program managing a team of senior consultants to deploy analytical solutions for the business by ideating, conceptualizing, developing and implementing the solution for various clients

- Manage working relationships with key business stakeholders; deepen and broaden existing engagements

- Demonstrate excellence in engagement delivery, insightful thought-leadership, strategic problem solving, high impact team management and strong client relations at senior executive levels

Desired Profile:

- 1-10 years of experience with Statistical Modeling and Predictive Analytics

- Versed in Logistic Regression based as well as other classification based model building and estimation of Probability of Default (PD), ws

- Experience/Knowledge of payments models

- Strong knowledge of Base SAS, preferably Advanced SAS and SQL skills

- Must have worked on high visibility projects in financial services (banking/insurance), retail, health care, telecom, utilities, media

- Knows how data should be made for modeling purposes

- How payments businesses (credit cards, loans, insurance) make money

- Who has done actuarial sciences and worked for Insurance company

- Clarity on datasets

- Knowledge of multicolinearity and correlation.

- Good communication, BD, managerial and leadership skills, client facing abilities etc. in addition to technical skills (marketing models, survival models, model validation).

Technical expertise:

- Use of analytics to solve business problems in the above domains

- Must have hands-on experience with data – need to understand data and showcase the same via interview

- Worked on modeling, clustering, segmentation, optimization problems or focused on machine learning or worked on a strategy role.