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Data Science - Machine Learning Internship in Chennai at CanGo Networks Private Limited

Data Science - Machine Learning

CanGo Networks Private Limited


Start Date Duration Stipend Posted On Apply By
3 Months ₹10000-15000 /Month 17 Apr'19 1 May'19
Full time
About CanGo Networks Private Limited (http://www.cangonetworks.com):
CanGo Networks is a Chennai based company that provides world-class network planning and optimization products and services for core and IP networks. CanGo Networks combines the expertise of IP and wireless technologies to enhance end-user experience and thereby increasing the profitability of the service providers.

Our flagship product OptiGo is deployed globally and is a pioneer in core network performance and optimization. OptiGo's big data and analytics platform enable network operators in delivering superior customer experience.
About the Internship:
- Statistical or machine learning techniques such as linear regression, logistic regression, and time series forecasting, clustering, etc. Deep learning knowledge is an added advantage.
- Statistical programming languages such as R or SAS is required. Other programming knowledge (Python, Perl, Java, C ) is highly desirable. Knowledge of SQL, databases, and cloud technology.
- Familiarity with big data tools and platforms (such as Hadoop, Hive, Hbase, MAPR,spark etc) is a big plus
- Should have done a live project or a certified course in the above-mentioned technologies.
- Candidates who have done data Science internships will get special preference.
# of Internships available: 7
Skill(s) required: Python (Learn Python), SQL, Algorithms, Machine Learning, Hadoop, R Programming and BIG DATA ANALYTICS
Who can apply:
Only those candidates can apply who:
  1. are available for full time (in-office) internship
  2. can start the internship between 17th Apr'19 and 17th May'19
  3. are available for duration of 3 months
  4. have relevant skills and interests
** Women willing to start/restart their career can also apply.
Certificate, Letter of recommendation, Flexible work hours, Informal dress code, 5 days a week, Free snacks & beverages.

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