Data Science Manager

1 month ago


Jakarta, Indonesia IlmuOne Data Full time

**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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