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Enable Data Incorporated

Data Scientist -Predictive Analytics & ML-( 8 Years)

Posted 18 Days Ago
Remote
Hiring Remotely in India
Mid level
Remote
Hiring Remotely in India
Mid level
The Data Scientist role involves predictive analytics, NLP, and Deep Learning with a focus on feature engineering for structured and text data.
The summary above was generated by AI

Data Science Lead (Predictive Analytics & ML):

Key Responsibilities

  • Lead and mentor a team of data scientists and analysts; provide technical guidance and ensure high-quality deliverables.
  • Design, develop, and optimize machine learning models (classification, regression, clustering, forecasting, etc.).
  • Build and maintain big data processing pipelines using PySpark, Spark SQL, and distributed computing environments.
  • Architect and deploy scalable ML solutions on Azure (Azure Databricks, Azure ML, ADLS, 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.

Required Skills

  • 5–8 years of hands-on experience in data science and ML development.
  • Strong hands-on experience in leading complex analytical problem solving using traditional ML architecture (like supervised and unsupervised learning, time series and Deep learning) along with strong team leadership capabilities.
  • Expertise in Python, PySpark, scikit‑learn, XGBoost, and related ML libraries.
  • Strong experience with Azure data and ML services.
  • Solid understanding of distributed computing and performance optimization using Spark.
  • Proven ability to lead technical teams, conduct code reviews, mentor juniors, and manage project execution.
  • Excellent communication, stakeholder management, and problem‑solving skills.
  • Experience with MLOps practices and CI/CD pipelines.

Top Skills

Azure
Databricks
Pyspark
PyTorch
TensorFlow

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