Vinay Kumar Yadav

Intro

15 years of experience in providing RAN Solution, RAN Data Analysis and building automation/ML Models to optimize/digitize the RAN Network. awesome work.

• Data analysis and provide solution for bottlenecks, capacity addition and expansion for RAN network.
• Analyzing and creating different automotive work to improve the RAN presales and RAN optimization work with the help of Python and ML Models
• Traffic profile benchmarking to analyze subscriber behavior.
• Involve with different functional domain to identify and propose the different Automation/data science scope.
• One of the key drivers of Ericsson Digitization program and developed 45+ Automation along with 15K hours of saving.
• Knowledge of industry best practices and a deep understanding on how data is extracted, transformed, scrubbed, and loaded in Data storage environments.
• Thorough understanding of Data Science tools, techniques and technologies in Machine Learning, NLP and Deep Learning algorithms using Python, Pandas, sklearn, NumPy, Matplotlib, Tensorflow and Keras,flask, SQL, pyspark etc
• Thorough understanding of algorithms like Regression, Clustering, NLP, Classification, including Time Series forecasting and Annova methods.
• Ability to deploy end to end Machine learning model.
• Basic Understanding of Docker and Kubernetes.
• Generating 100mSEK+ business each year thru analyzing/visualizing the RAN capacity data and providing the RAN solution.

Projects

• E2E Automation for Live KPI monitoring/Acceptance tracker/Packet Loss
  • Its Python based automation mainly used modules like Selenium, pandas, Paramiko, Matplotlib, smtplib etc.
  • Maintained a data pipeline that pulls data from several sources like BI,ENM and share points.
  • Create a live KPIs monitoring report and visualization for same.
  • Provide a high level of RCA also based on defined rules.
  • Share the details as summary on mail and upload all files on share point.
• ERCA-Ericsson Root Cause Analysis-ML Based
  • Its E2E project for providing root cause analysis for any KPI degradation in Worst cells to improvement/optimization of that KPIs.
  • Maintained a data pipeline that pulls data from several sources like BI, ENM and share points.
  • XG-Boost classifier used for classifying the correct RCA.
  • Further, Based on correct RCA its raising CR to Customer as E2E process.
• ML Based Data Traffic Forecasting
  • This Use case predict user experience metrics (Data Speed, Latency) so that operators can focus on improving performance
  • Its predict user experience metrics 24 hour in advance
  • P3/Umlaut data used as a data sources.
  • It’s a regression methodology to predict the 4G data Traffic load on the given training/test data.
• 2G/3G/4G/5G Presales Solution, design & planning
  • Providing presales Solution for RAN domain (gNodeb,eNodeB,NodeB,BSC & RNC)
  • Solution Document and BoQ preparation
  • HLD and LLD preparation.
  • RNC/HSPA/LTE Capacity analysis and provide solution for optimization.
  • RNC/HSPA/LTE Capacity analysis and provide solution for optimization.
  • Smartphone and MBB impact analysis.
  • Traffic profile benchmarking to analyse subscriber behaviour.
• AI RAN CHAT BOT
  • It’s a language processing and understanding model with pre-trained instances using Deep Learning.
  • It can communicate through both text and speech.
  • It trained with 2G/3G/4G/5G questions and able to answer most of the question
• Customer churn prediction in Telecom Sector
  • In this project, i have analyzed customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn
  • I build a machine learning model that is able to predict churning customers based on the features provided for their usage
  • Telecom churn prediction with 6 models-'Logistic Regression','KNeighbours','SVM','Adaboost','Decision Tree','Random Forest' is created in this project.
• ML based TR routing
  • ML based TR routing

Work Experiance

• Specialist-Data Science

Ericsson Global India | Nov 2012 - present
• Analyzing and creating different automotive work to improve the RAN presales and RAN optimization work with the help of Python and ML Models
• Involve with different functional domain to identify and propose the different data science scope.
• Participate in RAN Solution RFPs to provide effective and cost-effective solution thru Machine learning algorithms

• 3G Ran Planner

Nokia | Jul 2011 - Nov 2012
• KPI Data analysis with the help of MS Excel tools Preparation of HLD and LLD.

• Engineer 3G RAN

Ericsson Global India | March2010 - Jul 2011
• 3G data Analysis and proposing the bottleneck in the network
• Work on improvement of 3G network and provide solution

• Engineer RAN

RTL/Alcatel Lucent| Sept 2007 - March 2010
• KPI data report generation and provide the insight of the report thru MS excel graphs
• Collaborated with other team to take the action for improvement of network based on KPI data report

Certifications

• 5G RAN Certified associate from Ericsson
• 5G Tuning & Optimization Experiance Level
• Machine learning Fundamental from Ericsson
• Automation Experienced Certified from Ericsson
• Python for data Science_IITM
• Data Analytics with Python_IITR
• Online Certificate course in Data Science and Machine Learning from NIELIT
• Programming, Data Structures And Algorithms Using Python from IITM
• Introduction to internet of things from IIT Kharagpur
• Cloud Computing from IIT Kharagpur
• Big Data Computing from IIT

Awards

• 2x Ericsson Galactic/President Awards Winner
• 2x key contributor award winner
• 1x Employee Partnership Award
• 3x Ace Award Winner
• 5x Power Award Winner
• Generated many class A leads in Ericsson with business opportunity of 90mSEK and awarded for same.

Education Details

• University of Allahabad

Bachelor of Technology in Electronics and Communication in 2007 with 72%.

• IGNOU

MBA in Operation Management

• Symbiosis Centre for Distance Learning

Post Graduate Diploma in IT Management

Contact

   Phone-  +917838299924
   Mailto-  Vinay K Yadav - vinayjkit@gmail.com

• Twitter
• Linkedin
• Gmail
• GitHub

Elements

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