. The consultant will work closely with business stakeholders, product teams, and engineering groups to translate complex telecom data challenges into scalable, innovative AI-driven solutions that improve network performance, customer experience, and operational efficiency
Key Responsibilities
Project and Team Leadership
Collaborate with domain experts and business teams to identify and define AI/ML/GenAI use cases within telecom networks (e.g., anomaly detection, fault prediction, traffic forecasting, automated troubleshooting, knowledge assistants).
Lead cross-functional teams to deliver data science solutions, ensuring technical excellence and client satisfaction.
Independently manage end-to-end client engagements, including scoping, planning, delivery, and stakeholder communication.
Mentor junior team members and foster a collaborative, high-performance culture.
Translate business requirements into
AI-driven solution architectures and PoCs
aligned with design guidelines.
Generative AI Expertise
Translate business requirements into
AI-driven solution architectures and PoCs
aligned with design guidelines.
Provide technical consulting, present findings, and guide stakeholders on best practices for AI/ML adoption in telecom.
Design and deploy GenAI solutions (NLP, CV, multimodal) using advanced frameworks.
Architect agentic AI workflows with LangChain, LlamaIndex, AutoGen, and enterprise integrations.
Optimize AI agents and RAG pipelines (Pinecone, Weaviate, FAISS, Milvus) for accuracy and scalability.
Advise clients on GenAI adoption, aligning solutions with business objectives and tech ecosystems.
Cloud Platform Expertise
Design and deliver cloud-native AI/ML platforms on Azure, AWS, or GCP, ensuring scalability, security, and cost optimization across client environments.
Advise on MLOps best practices - from model training and deployment to monitoring and governance - leveraging platforms such as SageMaker, Azure Machine Learning, and Vertex AI.
Integrate AI solutions with enterprise data ecosystems, including data lakes, warehouses, and real-time pipelines.
Data Science and Engineering
Develop and scale advanced ML solutions (predictive modeling, recommendation engines, optimization algorithms) that directly impact business outcomes.
Lead the design of robust data architecture and feature engineering pipelines, supporting GenAI and ML applications across structured, unstructured, and multimodal datasets.
Business Impact and Innovation
Translate business challenges into actionable data science solutions with measurable outcomes.
Collaborate with business stakeholders to design data-driven strategies and identify opportunities for innovation.
Required Qualifications
Experience
: 4-8 years of experience in
data science / machine learning
, with at least 2 years applying AI/ML in telecom or network-related domains.
Education:
Master's Degree in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics, or related field).
Industry Knowledge:
Experience in
Telecom Network
Technical Skills
Proficiency in
Python, SQL, and ML frameworks
(TensorFlow, PyTorch, Scikit-learn).
Hands-on experience with
NLP, LLMs, and Generative AI frameworks
(LangChain, Hugging Face, Azure OpenAI, etc.).
Strong understanding of
telecom network data
(OSS/BSS, KPIs, alarms, logs, CDRs, performance counters).
Knowledge of
time series analysis, anomaly detection, and predictive modeling
in telecom scenarios.
Familiarity with
cloud platforms (Azure, AWS, GCP)
and
MLOps tools
for model deployment and monitoring.
Strong problem-solving, consulting, and stakeholder communication skills.
Preferred Skills
Experience in
5G/4G network analytics, RAN/Core KPIs, and SON use cases
.
Exposure to
knowledge graph techniques
for telecom use cases.
Prior experience working in
consulting / client-facing roles
delivering AI/ML solutions.
Contributions to
AI/ML/GenAI open-source projects or research publications
.
Experience:
5+ years in data science/Gen AI
Educational Qualification:
Master's or Bachelor's degree in Computer Science, Data Science, Statistics, Telecommunications, or related field.
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