Data Science Manager

Job Requirements:

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

Key Responsibilities:

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