Data Scientist - AI & ML
Summary
Leads AI/ML projects end-to-end, from problem definition to deployment, using Python, TensorFlow, and PyTorch to build models for forecasting, optimization, and anomaly detection, then collaborates with engineers and business teams to drive data-driven business decisions.
Company Overview
Headquartered in Singapore with offices in USA, Malaysia and India, we partner with multinational companies to deliver advanced technology and business process outsourcing solutions. We focus on customer needs to drive long-term growth and exceed client expectations.
Job Summary
Lead and manage the full lifecycle of Machine Learning and AI projects, delivering data-driven solutions that optimize business performance and operational efficiency.
Responsibilities
- Lead end-to-end Machine Learning and AI project lifecycles, including problem definition, data exploration, feature engineering, model training, validation, deployment, and performance monitoring
- Develop and implement ML, AI, or optimization models to solve business challenges such as performance improvement, demand forecasting, resource optimization, reliability enhancement, and customer experience
- Collaborate with data and software engineers to deploy ML/AI models in both air-gapped and cloud production environments
- Drive experimentation and continuous learning using AI techniques including time-series forecasting, anomaly detection, Computer Vision, and Natural Language Processing
- Present actionable, data-driven insights and recommendations to business users to inform decision-making
- Partner with Business Analysts to identify and assess high-impact AI use cases for feasibility and value
- Manage AI projects and maintain AI infrastructure to ensure operational stability and scalability
Preferred competencies and qualifications
- Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, Statistics, Data Analytics, Applied Mathematics, or a related field
- At least 8 years of relevant data science experience, including 2 or more years in a lead or senior technical role
- Proficiency in Python, Nifi, Airflow, SQL, and libraries such as pandas, numpy, scikit-learn, TensorFlow, PyTorch
- Experience with MLOps tools such as Databricks, Snowflake, and AWS Sagemaker
- Proficiency in data visualization tools including Power BI, Qlik, and Tableau