ilmuOne Data

Data Science Manager

Central Jakarta City, Jakarta, ID

27 days ago
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Summary

Job Requirements

  • Master’s or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • 5–10 years experiences in data science, with at least 2–4 years in a leadership or managerial role.
  • Proficiency in programming languages like Python, R, and SQL, and experience with machine learning libraries and frameworks.
  • Familiarity with data visualization tools (Tableau, Power BI), big data platforms (Hadoop, Spark), and cloud technologies (AWS, Google Cloud, Azure).
  • Strong communication, problem-solving, and stakeholder management skills.
  • Ability to align data science initiatives with business goals and deliver measurable outcomes.

Keys Responsibilities

  • Lead, mentor, and manage a team of data scientists, ensuring their professional growth and development.
  • Foster a collaborative and innovative team environment.
  • Provide technical guidance on advanced data science methodologies and tools.
  • Define and execute data science strategies aligned with organizational objectives.
  • Identify business challenges that can be addressed through data science and propose actionable solutions.
  • Prioritize and allocate resources to multiple data science projects.
  • Oversee end-to-end data science projects, from problem formulation and data acquisition to model development and deployment.
  • Ensure projects are delivered on time, within scope, and meet quality standards.
  • Lead the development and deployment of advanced statistical, machine learning, and AI models.
  • Work closely with business leaders, product teams, and other stakeholders to understand requirements and align data science solutions.
  • Build strong relationships across departments to promote data-driven decision-making.
  • Stay updated on the latest trends, technologies, and best practices in data science and AI.
  • Promote a culture of continuous learning and innovation within the team.
  • Collaborate with IT and data engineering teams to maintain robust data pipelines and infrastructure.
  • Present findings, models, and insights to executive management and other stakeholders.
  • Develop dashboards, visualizations, and reports to communicate data-driven insights effectively.
  • Provide recommendations to support strategic decisions based on data analysis.

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