Our client is a leading FMCG company who is looking for a qualified candidate to join their firm.Job description:Business Partnership: Collaborate with stakeholders to understand business challenges and translate them into data science initiatives with clear, measurable outcomes.End-to-End Model Development: Lead the full ML lifecycle, including data exploration, feature engineering, model building, tuning, and validation.Deployment & Scale: Oversee the deployment and operationalization of ML models in both batch and real-time environments, working closely with engineering teams.Model Monitoring & Improvement: Continuously monitor production models, addressing data drift, changing business needs, and ensuring long-term performance.Advanced ML Applications: Leverage structured and unstructured data (transactional, behavioral, textual, etc.) to design solutions such as recommendation engines, personalization systems, forecasting models, and NLP applications.Standards & Reusability: Establish and maintain reusable ML components, best practices, and frameworks to improve team efficiency and scalability.Communication & Influence: Present insights and solutions effectively to both technical and non-technical audiences, enabling data-driven decision-making.Team Leadership: Mentor junior data scientists, foster a culture of experimentation, and help grow the team’s technical and business capabilities.RequirementsBachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or related technical fields.Strong academic record (GPA ≥ 3.3/4.0) or background from a leading technical university.5+ years of hands-on experience in applied data science or ML engineering, including delivering production-grade models.Strong grounding in machine learning, applied statistics, and optimization techniques.Proficiency in Python and its data science ecosystem (e.g., scikit-learn, pandas, NumPy, XGBoost, LightGBM).Solid SQL skills with experience working on large-scale data platforms (Snowflake, BigQuery, Spark, or similar).Familiarity with modern MLOps workflows (MLflow, Airflow, Docker, CI/CD) and model monitoring practices.Strong problem-solving ability, product-oriented thinking, and capacity to thrive in a fast-paced, cross-functional environment.Contact: Huong DoDue to the immense number of applications, only shortlisted candidates will be contacted.
