Job Description :
Job Description
The Machine Learning engineer is responsible for developing machine-learning techniques for a wide variety of data sources, ranging from time series data to real time streaming data. The engineer will be engaged with projects that use both supervised and unsupervised learning and analyze multiple data sets – existing as well as data from new sources
Desired Skills:
Experience with ML techniques including supervised learning, clustering and classifiers
Good programming skills in Java/Python/Groovy, APIs (REST) and the open source ecosystem used in conjunction with machine learning toolkit
Professional experience building sophisticated models via regression, segmentation, decision tree, time series, design of experiments and other multivariate analysis
Excellent understanding of machine learning algorithms, such as SVM, Random Forests, Neural Network, etc.
Experience with common statistical and data science toolkits to extract and manipulate massive data sets, such as SAS, R, Matlab, SPSS, Python, H2O, etc.
Experience in using big data tools for analytics, and expertise in Hadoop ecosystem (HDFS, YARN, Spark, HBase, Hive, etc.
Experience with Apache Spark, Spark ML,H2O,Tensorflow
Ability to present insights/visualization using leading products such as Tableau, Qlik, or any open source software
Experience with Agile Delivery Methodology
Experience with Global Delivery Model with demonstrated knowledge of processes and methodologies
Ability to present at senior levels, and executive levels
Ability to work with diverse teams in various service lines, across multiple time zones.
Ability to be a part of and collaborate with multi-cultural teams
Prior experience of managing customer relationships, large data engagements across multiple domains is a must
Strong preference for a consulting background with a Big 4, IBM, Accenture, or other consulting firm.
Strong Communications, MSO or entertainment domain background is desired.
Willing to travel to different client locations
Description of Responsibilities
Create machine-learning based tools or processes for data mining and data analytics
Collaborate with business, engineering & product partners to implement machine learning usecases using big data storage, analytics and applications
Extending enterprise’s data with third party sources of information when needed
Translate business problems into machine learning usecases, develop statistical models and/or customized analysis to support business needs
Use advanced analytics to assess portfolio performance, identify business opportunities, and drive critical business decisions
Design data-driven marketing initiatives to manage customer relationship, drive sales, enhance executions, and increase productivity
Document analysis processes and results, summarize data insights, and present key findings to internal as well as external partners