Data Analyst - Machine Learning

Cognitive Computing

Quantitative: Skills to analyze data, and interpret analysis results in business in terms. This includes logical thinking, reasoning, hypothesis formulation, evidence-based evaluation, quantitative approximation and intuitive cross-validation. Ability to create scientific models for solving business problems from first principles is mandatory. Solid background of school-level mathematics is an absolute imperative. Formal training in, or experiential learning of, statistical methods and techniques would be necessary.

- Machine Learning: Skills to develop programmatic interventions to generate insights and develop cognitive systems. This includes skills to translate business problems to machine learning needs, design and develop machine learning systems for prediction, prescription. optimization and fact-based decisions, and tweak and train the models for accuracy improvement and automated self-adjustment.

It is required to have excellent programming skill in any one of the below languages, or good skills in any two languages from the following groups:

Object-Oriented: Java / C++

Procedural: Python / Perl / C/ Matlab / Octave / Fortran / Pascal

Special Purpose: R / SAS / SPSS / Matlab / Octave / Rapid Miner / Weka / Mahout / Spark / LISP

In addition, good understanding of feedback learning (e.g. reinforcement learning, Q-Learning, heuristic algorithms) would be helpful.

- Information Management: Skills to extract, transform, prepare and manipulate large datasets and unstructured content using standard RDBMS / SQL or big data and computing platforms like Hadoop / NoSql / Hbase / Pig / Hive.

Professional Expertise Skills to analyze data, and interpret analysis results in business in terms. This includes logical thinking, reasoning, hypothesis formulation, evidence-based evaluation, quantitative approximation and intuitive cross-validation. Ability to create scientific models for solving business problems from first principles is mandatory. Solid background of school-level mathematics is an absolute imperative. Formal training in, or experiential learning of, statistical methods and techniques would be necessary.

Skills to develop programmatic interventions to generate insights and develop cognitive systems. This includes skills to translate business problems to machine learning needs, design and develop machine learning systems for prediction, prescription. optimization and fact-based decisions

Object-Oriented: Java / C++

Procedural: Python / Perl / C/ Matlab / Octave / Fortran / Pascal

Special Purpose: R / SAS / SPSS / Matlab / Octave / Rapid Miner / Weka / Mahout / Spark / LISP

Hands-on analytics expertise, client-facing consulting experience, and acumen for solving business problems using quantitative methods. The responsibilities include application of hands-on analytics expertise and demonstration of thought leadership

- Expertise: Use of quantitative techniques / computational algorithms for any one of the following - Prediction / Forecasting / Prescription / Text Mining / Natural Language Processing.

Natural Language Processing

- Image / Video Processing

- Streaming Data Analytics

- Artificial Intelligence and Cognitive Systems

- Human Computer Interaction / Visualization