Machine Learning

Information Technology (IT) | Pune, India

 

We are looking for Machine Learning to join a growing client in Pune, India.

 

Requirements 

  • Data Scientist with strong hands on experience in “Big Data” as well as predictive modeling, optimization, machine learning, neural networks using a range of advanced technical tools (Python, SAS, Hadoop, R, Matlab, Machine learning, natural language processing tools, CPlex, C++, etc.).

 

Responsibilities 

  • To design and build models, preferably in R, Python or similar languages and To integrate multiple systems and data sets.
  • To link and mash up distinctive data sets to discover new insights which often requires connecting different types of data sets in different forms as well as being able to work with potentially incomplete data sources and cleaning data sets to be able to use them.
  • To be able to program, preferably in different programming languages such as Python, R, Java, Ruby, Clojure, Matlab, Pig or SQL.
  • To be responsible for helping develop quantitative solutions to solve complex applications.
  • To be involved in developing leading-edge, “out of the box” advanced analytic solutions and processes.

 

Skills & Experience 

  • Solid grounding in applied mathematics and statistics including expertise in several of the following (or related) techniques: text mining, recommendation analysis, outlier detection, predictive analyticsBayesian modeling, multivariate regression, logistic regression, machine learning, cluster analysis, decision trees, time series analysis and forecasting, factor analysis, structural equation modeling, item response theory, Markov chains, and data visualization.
  • Strong algorithmic and programming skills.
  • Capable of designing and programming new data mining algorithms.
  • Experience in developing big-data applications and analytics preferred.
  • Experience in Finance, Retail, or Digital Media industries.

 

About Talent Anywhere 

 

Talent Anywhere provides companies with comprehensive solutions to develop a global workforce. Our award winning model has been the most proven method for establishing and growing teams and offices in new locations. Since 2006, we have helped over 80 international companies deploy teams with over 2,000 employees globally.

 

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