Senior Data Scientist

About Renaissance InfoSystems

Renaissance Info Systems specializes in technology and digital recruitment, linking both contract and permanent IT professionals with companies throughout the Asia-Pacific region. Their strength lies in responsive communication and deep IT industry understanding, enabling them to build a robust network of skilled candidates.

Role Overview

The client’s Advanced Analytics & AI team transforms operational and commercial data related to parking, aeronautics, retail, and airport functions into actionable insights. As a Senior Data Scientist on an onsite contract basis, you will take full ownership of the most valuable data science projects from problem definition with business stakeholders through to model deployment and lifecycle management, acting as a key technical liaison between business teams and delivery groups spread both onshore and offshore.

Primary Responsibilities

• Lead the execution of forecasting and optimization projects, including modeling car park occupancy, price elasticity, valet resource allocation, passenger volume predictions over 18 months and 5 years, machine learning-driven security screening estimates, and retail performance and cross-selling models.
• Collaborate closely with business leaders across Parking, Commercial/Aeronautics, Retail, and Operations to frame business challenges, establish success criteria, and convert model findings into actionable strategies affecting pricing, capacity management, staffing, and revenue optimization.
• Develop, validate, and deploy models using Python in the Azure Machine Learning environment, integrating data from Snowflake.
• Maintain comprehensive accountability for model quality and lifecycle including feature engineering, interpretability analyses, scenario simulations, batch predictions, and monitoring models for data shifts and health post-deployment.
• Communicate forecasts, insights, and strategic recommendations effectively to senior leaders and executives, facilitating scenario analyses for critical decisions such as infrastructure development and pricing approaches.
• Provide technical leadership and mentorship to both onshore and offshore data science teams, reviewing their work and enhancing overall delivery standards.

Required Qualifications and Expertise

• Over 7 years of practical data science experience with a proven record of productionized models widely used by business stakeholders.
• Deep proficiency in Python including libraries like pandas and scikit-learn, coupled with strong SQL skills; solid experience with time series forecasting, regression, classification, and clustering techniques.
• Hands-on knowledge of enterprise machine learning platforms such as Azure ML and cloud data warehouses like Snowflake.
• Strong competence in MLOps practices encompassing model deployment, batch prediction pipelines, monitoring, detection of data drift, and retraining protocols.
• Experience working extensively within Microsoft Azure’s ecosystem including Azure ML, DevOps, and cloud storage/computing services.
• Excellent ability to engage stakeholders and translate complex data outcomes into strategic business trends and executive-level presentations.
• Academic credentials or equivalent practical experience in quantitative disciplines such as Statistics, Mathematics, Computer Science, Engineering, or Data Science.

Preferred Additional Skills

• Domain experience in aviation, transportation, pricing, revenue management, or forecasting-intensive operations.
• Familiarity with Power BI, explainable AI methodologies, optimization techniques, and frameworks for A/B testing.
• Understanding of Responsible AI principles and privacy-aware data analytics.
• Experience in leading and mentoring geographically distributed teams.

Technical Environment and Tools

The role involves practical use of Python, SQL, Microsoft Azure Machine Learning, Snowflake, Power BI, and the Azure Cloud platform.