We are seeking a highly skilled Data Science Project Manager to lead and coordinate data-driven projects from inception to completion.
This role involves collaborating with cross-functional teams, ensuring timely delivery of project milestones, and effectively communicating project status and insights to stakeholders.
Key Responsibilities:
Project Leadership:
- Define project scope, goals, and deliverables in collaboration with stakeholders.
- Develop detailed project plans, timelines, and resource allocation strategies.
- Ensure projects are completed on time, within scope, and within budget.
Stakeholder Management:
- Act as the primary point of contact for project stakeholders.
- Regularly communicate project progress, risks, and issues to stakeholders.
- Gather and incorporate feedback from stakeholders to refine project objectives.
Data Strategy:
- Collaborate with data teams to identify data needs and ensure quality data collection and management.
- Analyze and interpret data to drive business decisions and strategies.
Risk Management:
- Identify potential project risks and develop mitigation strategies.
- Monitor project progress and implement corrective actions as necessary.
Reporting and Documentation:
- Create comprehensive project documentation, including reports, dashboards, and presentations.
- Track project performance and report on key metrics to senior management.
Qualifications:
- Bachelor’s degree in Data Science, Computer Science, Business, or a related field (Master’s preferred).
- Proven experience in project management, particularly in data science or analytics.
- Strong understanding of data science methodologies, tools, and technologies (e.g., Python, R, SQL).
- Experience with project management tools (e.g., Jira, Trello, Asana).
- Excellent communication and interpersonal skills.
- Strong analytical and problem-solving abilities.
- Ability to manage multiple projects simultaneously and meet deadlines.
Preferred Skills:
- Experience in Agile methodologies.
- Familiarity with machine learning and statistical modeling.
- Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).