Data Scientist

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Data Scientist

Company Overview
A leading communications and digital services provider, this Singapore-based company delivers top-tier mobile, fixed, and broadband services, alongside advanced solutions for enterprises. The company specializes in providing data-driven communication solutions to government and corporate clients, incorporating artificial intelligence, cybersecurity, IoT, and robotics for enhanced connectivity and innovation.

Job Description
The Customer Lifecycle Management (CLM) team seeks a Data Scientist to drive data-driven strategies across customer acquisition, retention, and loyalty initiatives. In this role, the Data Scientist will apply advanced data science techniques, develop machine learning models, and conduct statistical analyses to support the team’s goal of optimizing the customer journey and increasing customer satisfaction. By transforming complex data into actionable insights, this role will be integral to shaping data-informed decision-making across the company’s customer lifecycle strategies.

Key Accountabilities

• Model Development: Build and refine machine learning models to predict customer behavior, churn, and lifecycle events.
• Data Analysis: Conduct exploratory and statistical analyses to uncover customer behavior patterns, validating insights to inform strategies.
• Data Visualization: Develop clear visualizations for complex insights and support dashboard maintenance.
• Machine Learning Pipelines: Assist in creating and managing pipelines for data preprocessing, model training, and deployment.
• Customer Segmentation: Apply clustering and segmentation to identify distinct customer groups, supporting targeted marketing strategies.
• Forecasting: Develop predictive models for behavior forecasts like purchase propensity and churn risk, improving model accuracy over time.
• Cross-Functional Collaboration: Engage with marketing, sales, and product development teams to align data projects with business goals.
• Continuous Learning: Stay updated on data science advancements, attending workshops and webinars.

Qualifications

• Education: Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field; Master’s preferred.
• Experience: 2-3 years in data science or machine learning, with solid statistical analysis and machine learning foundations.
• Technical Skills:
  • Proficiency in Python or R for analysis and modeling.
  • Skilled in SQL for data querying and manipulation.
  • Experience with visualization tools (e.g., Tableau, PowerBI, Matplotlib).
  • Knowledge of customer lifecycle metrics and concepts.
  • Familiar with machine learning libraries (scikit-learn, TensorFlow, PyTorch) and big data technologies (Hadoop, Spark).
  • Experience with version control systems (Git).

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