Data Scientist - Advance Analytics - BFSI

Candidate Description :

- Ability to understand business problems and design advanced statistical and analytical solutions independently

- Should be able to decide on the best machine learning/modeling/analysis techniques and provide actionable insights/ model algorithms to the business

- Demonstrated expertise in machine learning and advanced modeling techniques like Neural Networks, Deep learning, Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Logistic, Regression etc

- High level of proficiency in statistical tools and programming environments like Python, R, SAS, Big Data platforms like GreenPlum, Hadoop & Spark etc.

- Experience with Hadoop, relational databases and SQL is preferred.

- Exposure to Deep Learning applications and tools like Theano, Torch, Caffe and TensorFlow is preferred.

- Combine in-depth business knowledge, insights, and techniques such as data visualization, cross-tabs, statistical tests, and data mining techniques to identify customer or prospect needs, behavioral trends, product preferences, and up-selling, cross-selling, and retention opportunities

- Exhibits high degree of pro-activeness to work with tech teams to ensure deployment of models

- Work with tech groups to identify and resolve any data, infrastructure, or implementation issues

- Work with a consultative mindset to gather requirements from marketing sponsors and other team professionals to identify the right requirements

- Effective presentation and story boarding skills with exposure to executive level presentations

- Experience in managing partner relationships and overall program management

- Have the ability to discover new opportunities where analytical techniques can be leveraged for solving business problems.

Experience and Qualifications :

- 2-5 years of relevant experience with an organization known for its cutting edge/ best-in-class applicability of advanced analytics and predictive modeling techniques

- Master's Degree / PhD in a quantitative field (e.g., Computer Science, Economics, Engineering, Mathematics, Finance, Statistics, Operations Research)