22 Oct
InOrg Global
Palakkad
About the job
Overview: The Technical Project Manager, Data Science, is responsible for overseeing and coordinating data science projects from inception to completion. This role involves managing project timelines, collaborating with cross-functional teams, and ensuring the successful delivery of data-driven solutions that align with business objectives.
Job Description:
- Lead and manage data science projects, ensuring they are completed on time, within scope, and budget.
- Collaborate with data scientists, engineers, and business stakeholders to define project requirements, deliverables, and success criteria.
- Develop and maintain detailed project plans, outlining tasks, milestones, timelines, and resource allocation.
- Facilitate effective communication between project team members and stakeholders, ensuring clarity and alignment on project goals and progress.
- Monitor project progress, identify potential risks, and implement mitigation strategies to ensure project success.
- Ensure adherence to data science best practices and methodologies, promoting a high standard of work within the team.
- Provide regular updates to senior management, reporting on project status, risks, and outcomes.
- Foster a collaborative team environment, encouraging knowledge sharing and continuous improvement.
Qualifications:
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field. A Master’s degree or MBA is a plus.
- Experience in project management, with a focus on data science, analytics, or software development projects.
- Proven experience managing complex projects involving Machine Learning, Deep Learning, and AI.
- Strong understanding of data science and machine learning concepts,
with the ability to communicate effectively with technical and non-technical stakeholders.
Skills:
- Excellent project management skills, including planning, execution, risk management, and stakeholder communication.
- Proficiency with project management tools (e.g., Microsoft Project, JIRA, Trello).
- Strong leadership and team management abilities, with experience in guiding cross-functional teams.
- Effective communication skills, capable of conveying complex concepts clearly and concisely to various audiences.
- Solid understanding of data science principles and practices, with the ability to bridge the gap between technical teams and business stakeholders.
- Strong analytical and problem-solving skills,
with the ability to anticipate issues and develop effective solutions.
- Familiarity with Agile and Scrum methodologies, with experience applying these frameworks to data science projects.
- Knowledge of cloud platforms and big data technologies (e.g., AWS, Azure, GCP) is a plus.