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Lead AI Platform Operations Engineer- #AIDA
Singtel Group
Singapore
On-site
SGD 90,000 - 120,000
27 days ago
Junior Software Engineer - AI R&D Lab
Visier Solutions Inc
Singapore
On-site
SGD 70,000 - 100,000
28 days ago
Head of Application & AI Business
NETPLUZ ASIA PTE. LTD.
Singapore
On-site
SGD 100,000 - 150,000
28 days ago
Technical Project Manager for AI Singapore (Innovation)
NATIONAL UNIVERSITY OF SINGAPORE
Singapore
On-site
SGD 90,000 - 120,000
29 days ago
Connect with headhunters to apply for similar jobsIndustrial Data Science & AI Engineer
THALES SOLUTIONS ASIA PTE. LTD.
Singapore
On-site
SGD 60,000 - 80,000
29 days ago
Junior Data Architect Manager, AI & Data, Technology Consulting
Ernst & Young Advisory Services Sdn Bhd
Singapore
Hybrid
SGD 80,000 - 110,000
29 days ago
Junior SAP Developer (Senior Associate), AI & Data, Technology Consulting
Ernst & Young Advisory Services Sdn Bhd
Singapore
On-site
SGD 60,000 - 80,000
29 days ago
AI Centre of Excellence, Full-Stack Engineer (Generative AI)
KPMG Singapore
Singapore
On-site
SGD 70,000 - 90,000
30+ days ago
AI/Data/Machine Learning Engineer (Central / 5 days)
TALENTSIS PTE. LTD.
Singapore
On-site
SGD 70,000 - 100,000
30+ days ago
Head of Strategy & Capital Markets
HOME CONTROL SINGAPORE PTE. LTD.
Singapore
On-site
SGD 120,000 - 200,000
30+ days ago
PostSales/Solution Architect/PreSales (cloud)
DADACONSULTANTS PTE. LTD.
Singapore
On-site
SGD 80,000 - 120,000
30+ days ago
PhD Student (EDB-IPP Contract), Thermal Comfort & HVAC Control
Robert Bosch Group
Singapore
On-site
SGD 20,000 - 60,000
30+ days ago
Industrial Data Science & AI Engineer
-
Singapore
On-site
SGD 80,000 - 110,000
Full time
27 days ago
Job summary
A technology company in Singapore is seeking a Project Manager specializing in data science. Responsibilities include developing project plans, collaborating with stakeholders, and leading data analysis and machine learning model development. The ideal candidate holds a bachelor's degree in a related field and has proven experience in project management within industrial settings. This role offers a dynamic work environment with opportunities for mentorship and career growth.
Benefits
Company transport from designated MRT stations
Qualifications
- Proven experience in leading data science or analytics projects in industrial settings.
- Strong technical proficiency in data science tools and techniques.
- Excellent leadership, communication, and stakeholder management skills.
Responsibilities
- Develop comprehensive project plans for data science projects.
- Collaborate with stakeholders to leverage data science for business value.
- Lead data exploration and machine learning model development.
Skills
Project management
Data analysis
Machine learning
Stakeholder management
Data visualization
Technical leadership
Education
Bachelor's degree in computer science, data science, or related field
Tools
Flask
PowerBI
APIs
Job description
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
- Technical Leadership: Drive the design, development, and optimization of scalable data pipelines, APIs, and data platforms to support advanced analytics, AI, and business intelligence use cases.
- Dashboard & Visualization Solutions: Lead the development of enterprise-grade dashboards using Flask (or equivalent frameworks), ensuring usability, performance, and integration with data science models.
- Data for Digital Twin & Simulation: Architect and oversee the creation of data inputs for digital twin environments, enabling predictive simulations and real-time monitoring by integrating structured/unstructured inputs (JSON, XML, APIs).
- AI & Chatbot Integration: Design and implement intelligent assistant solutions, leveraging Retrieval-Augmented Generation (RAG) and related AI techniques to enhance knowledge discovery and automation.
- Data Strategy & Standards: Define best practices for data engineering, quality assurance, monitoring, and governance, ensuring compliance with enterprise and security standards.
- Collaboration & Mentorship: Work closely with cross-functional teams (data scientists, software engineers, product owners) while mentoring junior engineers to raise the team's technical capability.
Requirements
- Bachelor's degree in computer science, data science, industrial engineering, or a related field.
- 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.
- 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
- Proven track record of dashboarding and visualization (e.g., PowerBI, Flask, Plotly/Dash, or integration with BI tools) for decision-making support.
- Experience with digital twin simulation and real-time data integration, including structured/unstructured formats (JSON, XML) and APIs.
- Exposure to AI-driven solutions, especially chatbot development and Retrieval-Augmented Generation (RAG).
- Excellent communication and stakeholder management skills, with the ability to present complex technical concepts to non-technical audiences.
Other Information
- Work Location: Changi North Rise
- Working Days: Monday - Friday
- Company transport provided from designated MRT stations.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.
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