Senior Data Scientist

2 days ago

Ipswich, Suffolk, United Kingdom BULLIT SERVICES LIMITED Full time

Overview

· We are looking for an experienced Data Scientist with Telecom domain expertise to design, develop, and implement data-driven solutions for network optimization, customer experience enhancement, and business growth. The role involves working with large-scale telecom datasets, applying advanced analytics, and leveraging machine learning to solve critical business and network challenges.

·
Key Responsibilities

· Data Analysis & Modeling

· Analyze large-scale telecom data (CDRs, RAN/KPI data, OSS/BSS, billing, churn data).

· Build predictive and prescriptive models for network optimization, churn prediction, fraud detection, revenue assurance, and customer segmentation.

· Apply machine learning, deep learning, and statistical techniques to solve complex business problems.

· Feature Engineering & Data Preparation

· Perform data cleaning, transformation, and feature extraction from structured/unstructured telecom data.

· Work with big data platforms (Hadoop, Spark, Kafka, Hive, etc.) to process large telecom datasets.

· Visualization & Reporting

· Develop dashboards and reports for stakeholders using Tableau, Power BI, or Python visualization libraries.

· Translate insights into business recommendations for network planning, marketing, and customer experience teams.

· Collaboration

· Partner with network engineers, data engineers, product managers, and business analysts.

· Contribute to AI/ML-driven telecom initiatives like self-healing networks, anomaly detection, and predictive maintenance.

·
Required Skills & Qualifications

· –6 years of experience as a Data Scientist (telecom industry preferred).

· Strong knowledge of telecom data sources (RAN data, OSS/BSS, CDRs, CRM, subscriber behavior data).

· Hands-on expertise with machine learning frameworks (scikit-learn, TensorFlow, PyTorch).

· Strong proficiency in Python, R, SQL.

· Experience with Big Data & streaming platforms (Spark, Hadoop, Kafka, Confluent, etc.).

· Good understanding of statistical modeling, predictive analytics, and optimization techniques.

· Experience with cloud platforms (AWS, GCP, or Azure).

· Nice to Have

· Experience in AI/ML use cases for telecom (churn prediction, 5G optimization, anomaly detection in RAN, revenue assurance).

· Familiarity with time-series forecasting and real-time analytics.

· Knowledge of telecom protocols and KPIs (2G/3G/4G/5G, QoS, latency, throughput, handover metrics).

· Confluent Certified or Telecom Analytics certifications.

·
Education

· Bachelor's/Master's degree in Computer Science, Data Science, Statistics, or Telecommunications Engineering.

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