Enable Data

Enable Data

Enable Data is a leading provider of advanced data, software, and cloud engineering services, specializing in the implementation of large-scale data solutions such as Hadoop clusters and SAS applications to support critical business operations in the h...

IT Services
11-50
Founded 2018

Description

  • Lead and mentor a team of data scientists and analysts, providing technical guidance and ensuring high-quality deliverables.
  • Design, develop, and optimize machine learning models for classification, regression, clustering, forecasting, and related use cases.
  • Build and maintain big data processing pipelines using PySpark, Spark SQL, and distributed computing environments.
  • Architect and deploy scalable machine learning solutions on Azure, including Azure Databricks, Azure ML, ADLS, and ADF.
  • Oversee feature engineering, model lifecycle management, monitoring, and performance tuning.
  • Collaborate with cross-functional teams to translate business needs into analytical solutions.
  • Present insights, model outputs, and recommendations to technical and business stakeholders.
  • Lead technical teams, conduct code reviews, mentor junior team members, and manage project execution.

Requirements

  • 5–8 years of hands-on experience in data science and machine learning development.
  • Strong hands-on experience solving complex analytical problems using supervised and unsupervised learning, time series, and deep learning approaches.
  • Expertise in Python, PySpark, scikit-learn, XGBoost, and related machine learning libraries.
  • Strong experience with Azure data and machine learning services.
  • Solid understanding of distributed computing and performance optimization using Spark.
  • Proven ability to lead technical teams, conduct code reviews, mentor junior staff, and manage project execution.
  • Excellent communication, stakeholder management, and problem-solving skills.
  • Experience with MLOps practices and CI/CD pipelines.

Interested in this position?

Apply directly on the company website

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