Industrial Data Science Project Manager
2 weeks ago
Location: Singapore, Singapore
Thales people architect solutions that enable two-thirds of planes to take off and land safely. We create in-flight entertainment systems that engross 50 million fliers every year and we develop the avionics that control the world’s largest commercial aircrafts. Our simulators train the next generation of pilots for fighter jets, transporters and search and rescue helicopters. And, together, each and every member of our aerospace team makes a difference.
Thales established its presence in Singapore in 1973 to support the expansion of aerospace-related activities in the Asia-Pacific region. Throughout the last four decades, the company grew from strength to strength and is today involved in the primary businesses of Aerospace (including Air Traffic Management), Defence & Security, Ground Transportation and Digital Identity & Security. Thales today employs over 2,100 people in Singapore across all its business areas.
**Position Summary**:
- Thales Avionics (AVS) in Singapore consists of manufacturing and repair activities for aircraft OEM and airlines respectively.
- This position is responsible for leading data-driven projects aimed at optimizing industrial processes, improving efficiency, and driving innovation.
**Responsibilities**:
- Project Planning: Develop comprehensive project plans, defining scope, objectives, deliverables, timelines, resource allocation, and budget estimates for industrial data science projects.
- Stakeholder Engagement: Collaborate with stakeholders to understand business needs, operational challenges, and opportunities for leveraging data science to drive value.
- Data Acquisition and Preparation: Work with data engineers and domain experts to identify relevant data sources, extract, clean, and preprocess data for analysis and modeling.
- Data Analysis and Modeling: Lead data exploration, statistical analysis, and machine learning model development to uncover insights, patterns, and trends in industrial data.
- Model Deployment: Oversee the deployment of data science models into production environments, ensuring scalability, reliability, and integration with existing systems. Deploy standards defined and contribute to their improvements.
- Performance Monitoring: Establish key performance indicators (KPIs) and monitoring mechanisms to track the performance and effectiveness of deployed models over time with business value generated.
- Cross-Functional Collaboration: Coordinate with cross-functional teams, including data scientists, engineers, IT specialists, and business analysts, to ensure alignment and synergy in project execution.
- Risk Management: Identify and mitigate potential risks and challenges associated with data science projects, such as data quality issues, algorithmic bias, and model interpretability.
- Quality Assurance: Implement quality control measures and validation procedures to ensure the accuracy, robustness, and reliability of data science solutions.
- Documentation and Reporting: Maintain detailed documentation of project activities, methodologies, findings, and outcomes, and provide regular progress updates and reports to stakeholders.
- Business Value Delivery: Define, measure and keep track of business value deliverables link to the project ROI
**Requirements**:
- Bachelor's degree in computer science, data science, industrial engineering, or a related field; advanced degree or relevant certifications preferred.
- Min. 5 years proven experience in project management, specifically in leading data science or analytics projects in industrial settings.
- Experiences on requirement gathering, scoping, data mapping and data driven improvement, digital transformation projects to deliver business objectives are plus
- Strong technical proficiency in data science tools and techniques, including architecting, statistical analysis, machine learning, predictive modeling, and data visualization.
- Experience with industrial data sources, such as sensor data, time-series data, SCADA systems, and IoT devices.
- Excellent leadership, communication, and stakeholder management skills, with the ability to engage and influence both internal and external stakeholders at all levels of the organization.
- Proficiency in project management methodologies and tools
- Knowledge of industrial processes, manufacturing operations, and relevant industry standards and regulations.
- Familiarity with data governance, privacy, and security best practices in industrial environments.
- Experience with process optimization, continuous improvement, and lean manufacturing principles is a plus
- Experience with architecting, IS/IT projects or vendors management is a plus
- Strong disposition toward continuous learning, self-starter and passionate on data science to create business value
**Other information**:
- Working Location: Changi
- Working Hours: Monday - Friday, 9am - 6pm
- Company shuttle bus is provided at designated MRT stations
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