Data Scientist

Our client is a part of the international technology group with about 12,000 employees at more than 100 locations worldwide, Business Area Technologies stands for outstanding technologies and develops customized solutions in the areas of machinery, process equipment, software, measuring instruments, flavors, and services with a focus on the consumer products.

This role will be reporting to the Digital and Business Lead.

What you can expect from the role

Job Description:

• Utilize and enhance data mining techniques to extract usable data from valuable data sources (including internal systems, external APIs and third-party data) for developing analytic systems.
• Manage and maintain databases, ensuring that data is organized and structured in a way that supports efficient analysis.
• Pre-process large structured/unstructured datasets and variables, cleanse and validate data integrity and accuracy.
• Apply statistical techniques and advanced data analysis methods to understand patterns, trends, correlations and anomalies in data.
• Perform exploratory data analysis (EDA) to understand the features and characteristics of the data.
• Analyze massive data and establish prediction systems and algorithm models (e.g., machine learning/ deep learning/ AI/ classic statistical models) to optimize business processes and automate decision-making, particularly in industrial environments.
• Utilize algorithms such as regression, classification, clustering, decision trees, neural networks and ensemble methods.
• Validate models and fine-tune them for accuracy and performance using techniques like cross-validation, hyperparameter tuning and A/B testing.
• Use machine learning tools to select features, create and optimize classifiers.
• Build and optimize data applications in relevant production environment.
• Create visualizations, dashboards and reports to communicate and present findings/ results to both technical and non-technical stakeholders in a clear manner.
• Use tools such as Tableau, Power BI, Python (Matplotlib, Seaborn), or R (ggplot) for effective visual representation of data. Interpret data with explicit objectives for client business needs.
• Collaborate and support for digital software solutions and specific projects to complete data analyses and data visualization tasks as required (to tackle business challenges).
• Aligning data initiatives (data-related tasks and data-driven insights) with business decisions or goals by working closely with cross-functional teams.
• Experience working with large, complex datasets and cloud platforms, and applying machine learning techniques to real-world problems.

Job Requirement:

• Proficiency in programming languages such as Python, R, and SQL.
• Strong experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Knowledge of machine learning frameworks (e.g., Scikit-learn, TensorFlow, Keras).
• Familiarity with data visualization tools (e.g., Tableau, Power BI, D3.js).
• Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for data processing and model deployment.
• Solid foundation in statistics, probability theory and mathematical modeling to analyze complex datasets.
• Ability to design experiments and interpret results using statistical methods.
• Ability to think creatively and critically to tackle business problems with innovative data-driven solutions.
• Excellent problem-solving skills and attention to detail.
• Strong ability to clearly communicate complex technical concepts and insights to non-technical stakeholders.
• Ability to write clear reports and present findings effectively.
• Experience in certain specific domains (e.g., manufacturing, tobacco) can be a plus, as it allows for a deeper understanding of industry-specific challenges and datasets, e.g., ISA-95.
• Professional certifications (e.g., Coursera, edX, or similar) can be an added advantage.

Only shortlisted candidates will be contacted.

Valerie Song Lixuan

EA Registration No R1106569

Lic No.08C5436