Data Scientist, Machine Learning & MLOps

Smartone Telecommunications Holdings Limited

19 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English, Cantonese

Experience level

Intermediate

Data analysis

Information Engineering

Data Integrity

Python

Machine Learning

SQL Databases

Data Processing

Deep Learning

Model Validation

Build Management

PySpark

Information Technology

XGBoost

Machine Learning Operations

Software Version Control

Data Pipelines

ML Model Development & Deployment: Design, develop, and implement production-grade machine learning models (e.g., advanced tree-based, deep learning, clustering, and regression models) to solve critical business problems
MLOps & Pipeline Ownership: Architect, implement, and maintain robust ML Pipelines and MLOps frameworks to orchestrate seamless model development, version control, deployment, monitoring, and retraining in production environments
Business Impact & Revenue Generation: Directly drive business revenue and performance improvements by applying advanced data science techniques, ensuring all outcomes are measurable and aligned with organizational KPIs
Cross-Functional Collaboration & Storytelling: Partner closely with Marketing, Product, and executive teams to embed data-driven insights into campaign strategies and customer engagement. You will present complex findings clearly and persuasively to non-technical stakeholders, bridging the gap between deep technical analysis and business decision-making
Data Engineering for ML: Design and build efficient, scalable data pipelines using PySpark and other tools to collect, process, and transform massive, complex datasets, ensuring high data quality and accessibility for modeling
Innovation: Actively research, adapt, and apply the latest techniques and technologies in machine learning and MLOps to maintain a competitive edge

Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field. A Master's degree is highly preferred
A minimum of 3 years of hands-on experience in a Data Scientist role, with significant focus on building and deploying production-level ML models
Expert-level proficiency in Python (including ML libraries), SQL, and large-scale data processing tools like PySpark
Demonstrable experience with a wide array of machine learning algorithms (e.g., XGBoost, CNNs/RNNs, sophisticated clustering methods) and deep understanding of statistical inference and model validation in a live environment
Exceptional analytical and problem-solving skills with meticulous attention to detail and a commitment to data integrity
Proven ability to work independently, manage multiple projects simultaneously in a fast-paced, dynamic environment, and drive projects to timely completion
Fluent written and verbal communication skills in English and Cantonese are essential for effective collaboration with our diverse, local business teams