Developing and implementing advanced analytics approaches including statistical modelling, machine learning algorithms, text mining, regression, web analytics etc. to answer business questions and drive actionable insights.

×Work with very large Data Sets (both structured and unstructured) and design, develop and implement R&D and pre-product prototype solutions.

×Perform Data cleansing / transformation, feature engineering, apply statistical analysis, data visualization, data mining.

×Establish scalable, efficient, automated processes for model development, model validation, model implementation and large scale data analysis.

×Communicate analytical results in a way that is meaningful for business stakeholders and provides actionable insights.

 ×Any other relevant responsibility that may arise from time-to-time.

Skills Required:

×Should possess extensive knowledge of and experience in applying Data Mining and Machine Learning techniques in a project context

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

×Experience with common Data Science Toolkits such as Weka, NumPy, MatLab, etc {depending on specific project requirements}, Kaska, Spark.

×Proficiency in programming languages like Python, R, Java, C .

×Proficiency both in RDBMS and in using Query Languages such as Hive, Pig, SQL.

×Knowledge of Big Data platforms like Hadoop and its eco-system will be preferred.

×Experience with data visualisation tools, such as D3.js, GGplot, Tableau, etc.

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

×Good Communication skills.

×Data-oriented personality.