Senior data scientist

1 Hour ago • All levels • $80,000 PA - $122,000 PA

Job Summary

Job Description

The Senior Data Scientist will be responsible for understanding client requirements and leading the delivery of technical solutions, ensuring alignment with both client requirements and business objectives. Key responsibilities include developing and deploying machine learning models, predictive analytics, and AI solutions to solve business challenges. The role involves designing and optimizing algorithms for data processing, feature engineering, and pattern recognition, as well as leading data exploration, mining, and visualization to uncover trends and actionable insights. Collaboration with cross-functional teams is essential for integrating data science solutions into business strategies. The role also includes driving innovation by leveraging advanced statistical techniques, deep learning, and big data technologies, ensuring data integrity, governance, and best practices. Additionally, mentoring junior data scientists and promoting a data-driven culture, and staying ahead of industry trends and emerging technologies are key aspects.
Must have:
  • Develop and deploy machine learning models to solve business challenges.
  • Design and optimize algorithms for data processing and pattern recognition.
  • Lead data exploration and visualization to uncover insights.
  • Collaborate with teams to integrate data science solutions.
  • Drive innovation using advanced statistical techniques.
  • Ensure data integrity, governance, and best practices.
  • Mentor junior data scientists and promote data-driven culture.
  • Stay ahead of industry trends and emerging technologies.

Job Details

Job description:

To understand client requirements and lead the delivery of technical solutions ensuring alignment with client requirements and business objectives.

  • Key Responsibilities
    1. Develop and deploy machine learning models, predictive analytics, and AI solutions to solve business challenges.
    2. Design and optimize algorithms for data processing, feature engineering, and pattern recognition.
    3. Lead data exploration, mining, and visualization to uncover trends and actionable insights.
    4. Collaborate with cross-functional teams to integrate data science solutions into business strategies.
    5. Drive innovation by leveraging advanced statistical techniques, deep learning, and big data technologies.
    6. Ensure data integrity, governance, and best practices in model development and deployment.
    7. Mentor junior data scientists and promote a data-driven culture within the organization.
    8. Stay ahead of industry trends and emerging technologies to enhance analytical capabilities.

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