Remote Principal Data Scientist

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Encora

๐Ÿ“Remote - India

Job highlights

Summary

Join our dynamic team as a Principal Data Science Engineer to lead the development and implementation of advanced data science models and algorithms, drive innovation in data analytics, and collaborate with cross-functional teams to deliver high-impact solutions.

Requirements

  • Bachelorโ€™s or Masterโ€™s degree in Computer Science, Statistics, Mathematics, or a related field
  • 10+ years of experience in data science, with a proven track record of developing and deploying advanced models
  • Experience with Databricks
  • Proficiency in programming languages - Python, Pyspark
  • Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
  • Strong knowledge of statistical analysis, data mining, and predictive modelling. Machine learning algorithms (supervised/unsupervised/deep learning). Model evaluations & validation
  • Experience with big data technologies (e.g., Hadoop, Spark)
  • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and their data services. AWS knowledge is must
  • Docker, Kubernetes
  • Any DB experience, SQL query writing and optimization
  • Excellent problem-solving and analytical skills
  • Strong communication and interpersonal skills
  • Ability to work effectively in a fast-paced, dynamic environment

Responsibilities

  • Design, develop, and deploy advanced data science models and algorithms
  • Ensure models are scalable, maintainable, and optimized for performance
  • Lead and mentor a team of data scientists and engineers, providing technical guidance and support
  • Foster a culture of continuous learning and innovation within the team
  • Work closely with product managers, engineers, and business stakeholders to understand data requirements and deliver solutions
  • Collaborate with data engineering teams to ensure seamless integration of data science models into production systems
  • Stay current with the latest advancements in data science and machine learning
  • Evaluate and implement new tools, techniques, and technologies to enhance our data science capabilities
  • Conduct exploratory data analysis to uncover trends, patterns, and insights
  • Translate complex data into actionable insights and recommendations for business stakeholders
  • Lead data science projects from conception to completion, ensuring timely delivery and high-quality results

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