Details:

Job Description and Responsibilities:

- Work closely with the Product & Tech teams Selecting features, building and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods. 

- Doing the ad-hoc analysis and presenting results in a clear manner. 

- Extending company's data with third-party sources of information when needed. 

- Enhancing data collection procedures to include information that is relevant for building analytic systems. 

- Back-testing of new models and working with engineering teams to get systems to production. 

- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision 

Forests, etc. 

- Good applied statistics skills, such as distributions, statistical testing, regression, etc. 

- Proficiency in Python, R, Spark or related tools used for data handling to modeling to implementing. 

- Experience with common data science toolkits, such as Weka, NumPy etc. Excellence in at least one of these is 

highly desirable. 

- Experience in Credit modeling domain is very desirable. 

- Great communication skills Experience with data visualization tools, such as GGplot, etc. 

- Proficiency in using query languages such as SQL, Hive, Pig Experience with NoSQL databases, such as MongoDB, 

Cassandra, HBase is a plus. 

- Good scripting and programming skills. Aid in effectively integrating techniques and solutions developed with the base application. Python/Java skills are desirable. 

- Data-oriented personality, ability to work with high-level objectives and formalizing approaches and solutions. 

Min. Qualification:

pg

Skills Required:

data visualization, forecasting, hive, K-NN, machine learning, nosql, pig, python, regression, statistical modeling, svm