RESPONSIBILITIES

• Build and deploy analytics modules on various big data technology platforms
• Select features, build and optimize classifiers using machine learning
• Use state-of-the-art methods for data mining
• Optimize data with third-party information
• Enhance data collection procedures and include relevant and quality information to build analytics systems
• Conduct ad-hoc analysis and share the results in a comprehensible manner
• Create automated anomaly detection system and keep tracking its performance
• Plan and develop analytic projects in response to business needs
• Contribute to the development of data models and protocols for mining production databases
• Learn innovative data mining architectures, modelling standards, reporting, and data analysis methodologies
• Respond to and resolve data mining performance issues.
• Monitor data mining system performance and implement efficiency improvements

SKILLS

• 3-4 years of experience in data analytics
• Strong knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, and Decision Forests
• Experience working with data science toolkits such as R, Weka, NumPy, and MatLab (Excellence in at least one of these is highly desirable)
• Experience working with data visualization tools, such as D3.js and GGplot
• Proficiency in using query languages such as SQL, Hive, and Apache Pig
• Experience with NoSQL databases such as MongoDB, Cassandra, and HBase
• Good knowledge of statistical modeling
• Good scripting and programming skills
• Research and develop statistical learning models for data analysis
• Hands-on experience in Python, R, Java, and C++
• Proficiency in using big data technologies such as Hadoop and Spark
• Experience working with text analytics methods and/or tools
• Good knowledge of document classification, speech analytics, topic modeling, sentiment analysis
• Proficiency in risk analytics, marketing analytics, telecom analytics, retail analytics, e-commerce analytics, and so on