The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A Singapore-based global technology, defense, and engineering group with a long history was formally created in December 1997 through the merger of four listed Singaporean companies.
Senior Data Science Project Manager
Responsibilities:
Project Management & Leadership:
Oversees end-to-end execution of data science projects, ensuring alignment with business objectives.
Acts as both Project Manager and Scrum Master to facilitate efficient project delivery.
Organizes and manages project timelines, sprint planning, and progress tracking.
Fosters communication between stakeholders, teams, and clients to ensure transparency and success.
Strategic Planning & Business Process Analysis:
Analyzes business requirements and translates them into functional specifications for data science applications.
Defines key project goals, success metrics, and risk mitigation strategies.
Aligns data science initiatives with organizational priorities and operational workflows.
Data Science & Machine Learning Oversight:
Leads the deployment and operationalization of machine learning models and AI-driven solutions.
Works closely with data scientists to develop scalable and efficient data pipelines.
Ensures seamless integration of analytical models into production environments.
Team Leadership & Collaboration:
Mentors and guides data science teams, fostering professional growth and collaboration.
Establishes best practices for model deployment, data governance, and quality control.
Encourages a culture of experimentation, learning, and continuous improvement.
Technology & Infrastructure Management:
Oversees the adoption of best practices in MLOps, DevOps, and cloud infrastructure for data science projects.
Advocates for the use of scalable technologies and efficient workflows in data science development.
Ensures compliance with security policies, data privacy regulations, and industry standards.
Requirements:
Experience:
7+ years of professional experience managing data science, AI, or machine learning projects.
Proven track record of successfully leading and delivering complex data-driven solutions.
Experience working in cybersecurity, finance, healthcare, or other high-stakes domains is a plus.
Skills:
Expertise in data science methodologies, including machine learning, statistical analysis, and AI frameworks.
Strong proficiency in Python, with familiarity in ML frameworks like PyTorch.
Solid understanding of Data Science Architectures and DevOps practices.
Knowledge of CI/CD pipelines, model monitoring, and automation tools is a plus.
Leadership & Project Management:
Strong leadership skills with experience as a Project Manager or Scrum Master.
Proficiency in Agile methodologies and tools like Jira.
Excellent problem-solving, organizational, and communication skills.
Preferred Qualifications:
Certifications in Project Management or Agile methodologies (e.g., PMP, CSM) is a plus.
Experience in designing and deploying scalable data science solutions.
Disclaimer
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