VP - Network Performance Analytics

Role Title
Head – Network performance analytics
Position No
Function
Corporate-Technology
Sub Function/ Vertical/ Department
COG - SNOC
Band
M4
Reports to Role (Position No)
Service, performance & OSS Head
Location
Hyderabad
Date of last update/approval
Job Purpose (In one or two sentences)
SNOC is centralized technology operation centre responsible for FCAPS (Fault, Change, Accounting, Performance & Security) to serve Pan India mobility and enterprise customers across all technologies and domains through start of art tools, digital initiatives, well stitched processes and skilled people.
Network performance analytics vertical is responsible for onboarding, aggregation, collection, storage of network performance statistics across CORE, RAN, transmission, IP & Cloud in data lake and apply correlation with domain knowledge analytics to deduce actionable items. Generate business critical contractual documents pertinent to Field operations and RNA which are used for mandatory sign off before payments. Multiple aspects of job purpose are as follows -
Accountable for managing the network performance data and statistics in data lake, ensure reliable storage and the efficacy of the data/counters, aggregate, churn and massage data to deliver actionable in-sights and intelligence.
Responsible for continuous design, development, generation, validation and circulation of mobility network and enterprise services reports/statistics.
Responsible to produce business critical cross pollinated dashboards in line with contractual agreements for PAN India (each circle). The efficacy of these reports, followed by signoff across circles is basis of their successful delivery and payments worth hundreds of millions.
Uphold network experience expectation through highest quality of efficacy, consistency, digital mind-set and simple yet effective processes
AI/ML-enabled performance intelligence – Lead the transformation of network performance analytics through AI/ML, GenAI, predictive analytics and intelligent automation. Build and scale AI-enabled applications that proactively detect anomalies, forecast traffic and capacity, support root-cause analysis, automate reporting and convert complex network data into actionable operational and business insights
Key Accountabilities / Key Result Areas (Max 5)
Network data management – Responsible for managing performance and alarm data for 770K network elements, process billions performance data records worth TB data per day and million alarms data points. Manage Hadoop data from 550+ OSS servers. Plan, engineer and operationalize onboarding - Node – Life cycle mgmt (MACD) – Move, Add, Change & Delete in tools like MYCOM, SEVONE, Accedian etc. Design and follow processes and best practices to ensure exhaustive coverage and efficacy of data.
Network data analytics - Responsible for data aggregation and correlation with domain knowledge analytics to deduce actionable insights and intelligence across mobility (CORE, RAN, transmission, IP & Cloud) and Enterprise. Provide multi angles of attack in data statistics to analyze the performance and fault issues faster. Ensure design, development, generation, validation and circulation of more than 100+ performance data reports containing more than 10K tabs, helping PAN India optimization engineers to take insights and act for network experience improvement. Ensure requisite analytics for enterprise customers and technical service managers.
Business critical dash boarding for signoff – Ensure data analytics by NOC is single source of truth. Generate validated business critical contractual documents pertinent to Field operations and RNA which are used for mandatory sign off before payments for field and MS contracts.
Compliance – Accountable to adhere NOC processes under ITIL framework to ensure predictable outcome of the highest qualit4y every single time, hence keep the SNOC operation organization complied with ISO 20K (Service Management System), ISO 27K (Information Security Management Standards),TL 9K and other compliances like SOX, TRAI/DOT, PIM etc. Bring in Service excellence through continual service improvement & ensure network reliability by process optimization and simplification.
Health, Safety & well being - Build a safe and conducive work environment through exercise of HSW controls. B uild the best team fostering Digital DNA, inclusivity & diversity
AI/ML and advanced analytics transformation – Define and execute the AI/ML roadmap for RAN, Core, Transmission, IP, Cloud, Enterprise and service performance analytics. Identify high-value use cases, lead development from proof of concept to production, establish reusable AI capabilities, and ensure measurable improvement in productivity, service availability, customer experience and decision-making.
AI application ecosystem and governance – Lead the design and delivery of AI-enabled applications using enterprise data, cloud/on-premise AI platforms, APIs, data lakes, MLOps and GenAI/LLM ecosystems. Establish controls for data quality, model accuracy, explainability, security, responsible AI, lifecycle monitoring and continuous retraining
Core Competencies, Knowledge, Experience, Technical / Professional Qualifications (Max 5)
Overall 15-20 years of experience in managing telecom networks and minimum 5 years of managing data analytics across domains – VoLTE, Packet CORE, Cloud, IN/VAS, IP/MPLS, SDN controllers, OSS, Transmission, Enterprise etc
Experience of handling performance and experience management systems.
Adept in information management systems, evaluate end-user requirements, along with domain knowledge to convert information to in-sights and intelligence.
Strong understanding & experience in generation of operational KPIs and related analytics
AI/ML capability – Strong understanding of Artificial Intelligence, Machine Learning, Deep Learning, Generative AI and advanced analytics, with experience in translating telecom operational problems into scalable AI use cases and applications.
AI application delivery experience – Demonstrated experience in building and operationalizing AI-enabled applications using an AI ecosystem comprising data engineering, Python/Spark-based analytics, ML frameworks, APIs, cloud or on-premise platforms, model repositories and MLOps pipelines.
Telecom AI use cases – Experience with use cases such as traffic and capacity forecasting, anomaly detection, predictive maintenance, alarm correlation, service-impact analysis, customer-experience analytics, root-cause analysis and intelligent automation.
Delivery and stakeholder leadership – Ability to lead cross-functional teams of network experts, data engineers, data scientists, application developers and technology partners, and to industrialize AI use cases from business requirement and PoC through deployment, adoption and benefit realization.
Technical / Professional Qualifications -
Electronics/Telecommunication engineering graduate – Must
Expert in information management systems - Must
Should have knowledge of ITIL processes and industry certificates – Must
4G/5G technology, Radio & wireless networking, Transmission & IP-MPLS, CS-Core and VoLTE, Packet core (SGSN, MME, GGSN, SGW, PGW), Enterprise services (MPLS, ILL, NPLC, Multi-VRF, SD-WAN, SIP-PRI, etc) – Must
Digital mint set - Preferred
Business and Financial acumen – Preferred
Key Performance Indicators (Max 5)
Operational Performance
Error free analytics and reporting >99.5%
Analytics coverage >99.9%
Timely delivery >99%
ZERO NC for all ISO External and Internal Audits – ISO 20K,27K,TL9000,TRAI etc.
Development Performance
Attrition to be maintained below 15%
70 Hours training each candidate per year
Building of rockstars and dream teams each quarter
Future Ready
Build 10% efficiency YOY with focussed approach on automations
Conceive and implement simplified yet effective operation processes
AI value realization – Deliver an agreed portfolio of AI/ML use cases into production with defined adoption, accuracy, productivity and service-performance benefits.
Model and application reliability – Maintain agreed thresholds for data quality, model accuracy, availability, explainability and monitoring of production AI applications
Annual Budget Owned / Key Quantitative Parameters like Workforce managed etc.
Operational Parameters
Performance and alarm data for 770K network elements.
Process 48 billion performance data records worth 170 TB data per day.
Storage across 1200 TB.
15 million alarms data points.
Extracts value out of CAPEX and OPEX equivalent to 150 Cr INR.
Manage Hadoop data equivalent to 250 TB from 550+ OSS servers
100+ performance data reports containing more than 10K tabs
Workforce Parameters
51 with a break up as below -
On-Role : 41 (With 4 Proposed M3 roles)
Off-role : 10
Risks, Challenges, Job Context (Short Description)
Risks & Challenges

Work arrangement
No