Job Description
We are looking for a Python Developer with expertise in data analytics and machine learning, specifically within the telecom industry. If you have a passion for handling large-scale datasets, building predictive models, and optimization for data retrieval, this role is for you.
Key Responsibilities
- Develop and optimize data processing pipelines using Pandas, VAEX, and NumPy for telecom datasets.
- Implement machine learning models for fraud detection, traffic anomaly detection, and predictive analytics.
- Work with structured and unstructured telecom data, including CDRs (Call Detail Records) and network logs.
- Manage and optimize Elasticsearch clusters, including indexing, data ingestion, query tuning, and performance optimization.
- Design and develop custom analytics dashboards using Kibana, Metabase, BI Tools etc. for real-time telecom insights.
- Perform ETL operations for cleaning, transforming, and analyzing telecom data efficiently.
- Develop predictive analytics solutions for customer behaviour, churn prediction, and call routing optimization.
- Integrate with big data frameworks (e.g., Apache Druid, BigQuery) for large-scale telecom data analytics.
- Optimize code performance for real-time processing of high-volume datasets.
- Collaborate with cross-functional teams to improve data insights, reporting, and decision-making for telecom clients.
Required Skills & Qualifications
- Strong Python programming skills with hands-on experience in Pandas, VAEX, NumPy, and Scikit-learn.
- Expertise in data analytics and visualization for large telecom datasets.
- Proven experience in Elasticsearch – managing indices, writing queries (KQL, DSL), optimizing search performance, and handling large-scale data ingestion.
- Proficiency in machine learning techniques, including classification, clustering, and anomaly detection.
- Experience working with telecom data sources such as CDRs, network logs, and fraud detection systems.
- Familiarity with SQL and NoSQL databases (e.g., PostgreSQL, BigQuery, Elasticsearch).
- Experience with data engineering tools (e.g., Apache Spark, Dask) is a plus.
- Strong communication skills to convey technical insights clearly and collaborate with cross-functional teams.
- Ability to thrive in a fast-paced, data-driven environment, optimizing performance for high-volume data processing.
Preferred Qualifications
- Knowledge of VoIP technologies (SIP, RTP, PBX, Asterisk, FreeSWITCH) is a plus.
- Experience deploying Elasticsearch and training ML models on cloud platforms (AWS, GCP, Azure).
- Familiarity with Kafka, RabbitMQ, or other message queues for streaming data analytics.
- Hands-on experience with Kibana for visualizing telecom data trends and alerts.
- Experience developing REST APIs for data retrieval and automation.