Data Analyst/Ai Engineer
· Location: Penang
· Experience: 4+ yrs
· Mode: 1 Year contract under us, either extendable / convertible
· Prefer: Semicon/Electronics domain
· Interview rounds: 1 or 2 (Virtual)
· Availability: Immediate - 30 days
Position Summary
We are seeking a highly motivated Data Scientist to support Research & Development (R&D) initiatives by applying advanced analytics, statistical methods, and machine learning techniques to solve complex engineering and scientific challenges. The successful candidate will collaborate with cross-functional teams to transform data into actionable insights, enable data-driven decision-making, and contribute to the development of innovative technologies and products.
Key Responsibilities
- Conduct data-centric evaluations, analytical studies, and statistical analyses to support R&D projects, technology development, and validation activities.
- Collaborate with multidisciplinary R&D teams to translate engineering and scientific challenges into robust analytical and data-driven solutions.
- Develop scalable data pipelines and perform data processing, exploration, and advanced analytics using Cloud and Big Data technologies.
- Design and deliver clear, impactful visualizations, dashboards, and analytical reports to effectively communicate insights to both technical and non-technical stakeholders.
- Ensure data quality, integrity, consistency, and traceability by implementing sound data management and governance practices.
- Apply statistical analysis, machine learning, and predictive modeling techniques to generate actionable business and technical insights.
- Contribute to the continuous improvement of data science methodologies, analytical frameworks, tools, and best practices within the R&D organization.
- Support the deployment, automation, and maintenance of analytical models and solutions where applicable.
- Promote knowledge sharing, documentation, and reproducible analytics across project teams.
Qualifications
Education
- Bachelor's, Master's, or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Physics, Engineering, or related quantitative discipline.
Experience
- Experience working in research, engineering, manufacturing, electronics, or other technology-driven environments with a demonstrated focus on delivering measurable business value.
- Proven experience managing end-to-end analytics projects, including:
- Data acquisition and ETL processes
- Data preparation and feature engineering
- Statistical analysis and machine learning model development
- Model deployment and automation
- Results visualization and stakeholder reporting
- Familiarity with Agile methodologies and collaborative project delivery.
- Primarily an individual contributor with the ability to lead workstreams, mentor junior colleagues, and influence cross-functional teams without formal authority.
- Experience collaborating with global and multicultural teams across multiple locations and time zones is advantageous.
Technical Competencies
- Strong foundation in statistics, machine learning, and predictive analytics, including:
- Regression and classification
- Time-series analysis
- Clustering techniques
- Optimization methods
- Experimental design
- Model validation and performance evaluation
- Proficiency in structured problem-solving methodologies (e.g., CRISP-DM), hypothesis-driven analysis, reproducible analytics, peer review, and documentation.
- Experience implementing data quality controls, governance standards, and traceability practices.
- Strong programming skills in Python (Pandas, NumPy, Scikit-learn) and/or SQL.
- Experience with Big Data technologies such as Apache Spark or Databricks is preferred.
- Familiarity with Cloud platforms including Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) is an advantage.
- Working knowledge of Git, APIs, Docker, and CI/CD concepts is desirable.
- Experience developing dashboards and visualizations using Power BI and/or Tableau.
Core Competencies
- Excellent analytical thinking and structured problem-solving skills.
- Strong communication and data storytelling abilities, with the capability to present complex analyses to diverse audiences.
- Effective stakeholder management and cross-functional collaboration skills.
- Curiosity, continuous learning mindset, and adaptability in dynamic R&D environments.
- Ability to translate engineering and scientific problems into practical analytical solutions.
- High level of professionalism, integrity, and confidentiality when handling sensitive information.
- Proactive mindset focused on continuous improvement and operational excellence.
- Willingness to travel occasionally, as business needs require.
Language Requirements
- Fluent English (spoken and written).
Additional local language(s) will be considered an advantage.
