Data Science Engineer

Ericsson

India

On-site

INR 900,000 - 1,800,000

Full time

14 days+
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Job summary

Ericsson in India is seeking a data scientist to work with data science methodologies to solve telecom and technology infrastructure problems. You will build and maintain predictive models and develop scalable data solutions to improve business intelligence and operational efficiency.

You will design data pipelines, implement ML solutions for classification, regression and clustering, and create visualizations to communicate findings to stakeholders.

Qualifications

  • Experience with data science methodologies in telecom/tech.
  • Ability to build predictive models driving BI and ops efficiency.
  • Collaborate with cross-functional teams to translate insights into actions.
  • Develop and optimize large-scale data algorithms.

Responsibilities

  • Design data pipelines and ETL processes for diverse sources.
  • Create visualizations and dashboards for stakeholders.
  • Implement ML solutions for classification, regression, and clustering tasks.
  • Evaluate model performance and iterate based on validation results.

Skills

Data science
Predictive modeling
ETL
Visualization
ML algorithms
Model evaluation

Tools

Python
R
Spark

Job description

Batch: 2020/2021/2022/2023/2024/2025/2026.

About the role:
  • Work with data science methodologies to solve complex problems within telecommunications and technology infrastructure
  • Build and maintain predictive models that drive business intelligence and operational efficiency
  • Collaborate with cross-functional teams to translate data insights into actionable recommendations
  • Develop and optimize algorithms for large-scale data processing and analysis
What you’ll work on:
  • Designing data pipelines and ETL processes to handle diverse data sources
  • Creating visualizations and dashboards that communicate findings to stakeholders
  • Implementing machine learning solutions for classification, regression, and clustering tasks
  • Evaluating model performance and iterating on approaches based on validation results
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