The Candidate should be have: - good understanding of Statistical concepts - worked on Data Analysis and Model building for 1 year - ability to implement Data warehouse and Visualisation tools (IBM, Amazon or Tableau) - use of ETL tools - understanding of scoring models The candidate will be required: - to build models for approval or rejection of loans - build various reports (standard for monthly reporting) to optimise business - implement datawarehosue The candidate should be self-starter as well as work without supervision. You will be the 1st and only employee for this role for the next 6 months.
1 to 3 years of experience in product analytics - Highly conversant with Google Analytics and other similar tools - Basic programming ability(preferably R or Python)
Primary Skills : - B.Tech/MS/PhD degree in Computer Science, Computer Engineering or related technical discipline with 3-4 years of industry experience in Data Science. - Proven experience of working on unstructured and textual data. Deep understanding and expertise of NLP techniques (POS tagging, NER, Semantic role labelling etc). - Experience working with some of the supervised/unsupervised learning ML models such as linear/logistic regression, clustering, support vector machines (SVM), neural networks, Random Forest, CRF, Bayesian models etc. The ideal candidate will have a wide coverage of the different methods/models, and an in depth knowledge of some. - Strong coding experience in Python, R and Apache Spark. Python Skills are mandatory. - Experience with NoSQL databases, such as MongoDB, Cassandra, HBase etc. - Experience of working with Elastic search is a plus. - Experience of working on Microsoft Azure is a plus although not mandatory. - Basic knowledge of Linux and related scripting like Bash/shell script. Role Description (Roles & Responsibilities) : - Candidate will research, design and implement state-of-the-art ML systems using predictive modelling, deep learning, natural language processing and other ML techniques to help meeting business objectives. - Candidate will work closely with the product development/Engineering team to develop solutions for complex business problems or product features. - Handle Big Data scale for training and deploying ML/NLP based business modules/chatbots.